scholarly journals Socioeconomic inequalities in hypertension in Kenya: a decomposition analysis of 2015 Kenya STEPwise survey on non-communicable diseases risk factors

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Samwel Maina Gatimu ◽  
Thomas Wiswa John
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Socioeconomic Factors ◽  
Body Mass ◽  
Concentration Index ◽  
Socioeconomic Inequality ◽  
Decomposition Analysis ◽  
Socioeconomic Inequalities ◽  
Non Communicable Diseases

Abstract Background One in four Kenyans aged 18–69 years have raised blood pressure. Despite this high prevalence of hypertension and known association between socioeconomic status and hypertension, there is limited understanding of factors explaining inequalities in raised blood pressure in Kenya. Hence, we quantified the socioeconomic inequality in hypertension in Kenya and decomposed the determinants contributing to such inequality. Methods We used data from the 2015 Kenya STEPwise survey for non-communicable diseases risk factors. We included 4422 respondents aged 18–69 years. We estimated the socioeconomic inequality using the concentration index (C) and decomposed the C using Wagstaff decomposition analysis. Results The overall concentration index of hypertension in Kenya was − 0.08 (95% CI: − 0.14, − 0.02; p = 0.005), showing socioeconomic inequalities in hypertension disfavouring the poor population. About half (47.1%) of the pro-rich inequalities in hypertension was explained by body mass index while 26.7% by socioeconomic factors (wealth index (10.4%), education (9.3%) and paid employment (7.0%)) and 17.6% by sociodemographic factors (female gender (10.5%), age (4.3%) and marital status (0.6%)). Regional differences explained 7.1% of the estimated inequality with the Central region alone explaining 6.0% of the observed inequality. Our model explained 99.7% of the estimated socioeconomic inequality in hypertension in Kenya with a small non-explained part of the inequality (− 0.0002). Conclusion The present study shows substantial socioeconomic inequalities in hypertension in Kenya, mainly explained by metabolic risk factors (body mass index), individual health behaviours, and socioeconomic factors. Kenya needs gender- and equity-focused interventions to curb the rising burden of hypertension and inequalities in hypertension.

scholarly journals Socioeconomic inequalities in hypertension in Kenya: A decomposition analysis of 2015 Kenya STEPwise survey on non-communicable diseases risk factors

2020 ◽  
Author(s):  
Samwel Maina Gatimu ◽  
Thomas Wiswa John
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Socioeconomic Factors ◽  
Body Mass ◽  
Concentration Index ◽  
Socioeconomic Inequality ◽  
Decomposition Analysis ◽  
Socioeconomic Inequalities ◽  
Non Communicable Diseases

Abstract Background: One in four Kenyans aged 18–69 years have raised blood pressure. Despite this high prevalence of hypertension and known association between socioeconomic status and hypertension, there is limited understanding of factors explaining inequalities in raised blood pressure in Kenya. Hence, we quantified the socioeconomic inequality in hypertension in Kenya and decomposed the determinants contributing to such inequality.Methods: We used data from the 2015 Kenya STEPwise survey for non-communicable diseases risk factors. We included 4,422 respondents aged 18–69 years. We estimated the socioeconomic inequality using the concentration index (C) and decomposed the C using Wagstaff decomposition analysis.Results: The overall concentration index of hypertension in Kenya was −0.08 (95% CI: −0.14, −0.02; p = 0.005), showing socioeconomic inequalities in hypertension disfavouring the poor population. About half (47.1%) of the pro-rich inequalities in hypertension was explained by body mass index while 26.7% by socioeconomic factors (wealth index (10.4%), education (9.3%) and paid employment (7.0%)) and 17.6% by sociodemographic factors (female gender (10.5%), age (4.3%) and marital status (0.6%)). Regional differences explained 7.1% of the estimated inequality with the Central region alone explaining 6.0% of the observed inequality. Our model explained 99.7% of the estimated socioeconomic inequality in hypertension in Kenya with a small non-explained part of the inequality (−0.0002).Conclusion: The present study shows substantial socioeconomic inequalities in hypertension in Kenya, mainly explained by metabolic risk factors (body mass index), individual health behaviours, and socioeconomic factors. Kenya needs gender- and equity-focused interventions to curb the rising burden of hypertension and inequalities in hypertension.

scholarly journals Socioeconomic Inequalities in Hypertension in Kenya: A Decomposition Analysis of 2015 Kenya STEPwise Survey on Non-communicable Diseases Risk Factors

2020 ◽  
Author(s):  
Samwel Maina Gatimu ◽  
Thomas Wiswa John
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Socioeconomic Factors ◽  
Body Mass ◽  
Concentration Index ◽  
Socioeconomic Inequality ◽  
Communicable Diseases ◽  
Socioeconomic Inequalities ◽  
Non Communicable Diseases

Abstract IntroductionOne in four Kenyans have raised blood pressure. Despite this high prevalence of hypertension and known association between socioeconomic status and hypertension, there is a paucity of evidence on inequality in raised blood pressure in Kenya. Hence, we quantified the socioeconomic inequality in hypertension in Kenya and decomposed the determinants contributing to such inequality.MethodsWe used data from the 2015 Kenya STEP wise survey for non-communicable diseases risk factors. We included 4,398 respondents aged 18–69 years. We estimated the socioeconomic inequality using the concentration index (C) and decomposed the C using Wag staff decomposition analysis.ResultsThe overall concentration index of hypertension in Kenya was − 0.08 (95% CI: −0.14, − 0.02; p = 0.007), showing socioeconomic inequalities in hypertension disfavouring the poor population. Half (52.8%) of the pro-rich inequalities in hypertension was explained by body mass index (52.8%) while 21.1% by socioeconomic factors (paid employment (9.3%), education (7.7%) and poorest wealth quintile (4.1%)) and 17.6% by demographic factors (female gender (11.8%), age (5.2%) and marital status (0.6%)). Regional differences explained 8.1% of the estimated inequality with the Central region alone explaining 6.9% of the observed inequality. Our model explained 98.3% of the estimated socioeconomic inequality in hypertension in Kenya with a small non-explained part of the inequality (− 0.001).ConclusionThe present study shows substantial socioeconomic inequalities in hypertension in Kenya, mainly explained by metabolic risk factors (body mass index), individual health behaviours, and socioeconomic factors. Kenya needs gender- and equity-focused interventions to curb the rising burden of hypertension and inequalities in hypertension.

scholarly journals Prevalence and Determinants of High Blood Pressure among Adolescents: A School based Study in Rural Area of Hooghly District, West Bengal

2021 ◽  
Vol 8 (11) ◽  
pp. 205-210
Author(s):  
Malay Kumar Das ◽  
Rabindranath Sinha ◽  
Aparajita Dasgupta
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Food Intake ◽  
Alcohol Consumption ◽  
Body Mass ◽  
High Blood Pressure ◽  
Fast Food ◽  
Non Communicable Diseases

Introduction: The World Health Organization has already warned of increasing non-communicable diseases among adolescents as a major public health problem. The importance of this age group also lies in the fact that many serious diseases in adulthood have their roots in adolescence. Method: A pre-designed and pre-tested questionnaire was used in class-room setting to collect information from students regarding presence of risk factors of non-communicable diseases. The respondents were also subjected to anthropometric measurements and blood pressure examination using standard operating procedures. Results: A total of 761 students of class VI-XII participated in the study of which 61.4% were boys and rests were girls. High blood pressure among boys and girls were 19.9% and 22.1% were respectively. In Bivariate analysis age > 15 years (median) (OR= 2.11), fast food intake (>3 times/week) (OR= 1.66), Alcohol consumption (OR= 2.22), less physical activity (OR=1.54), increased body mass index (OR=2.53), significantly associated with high blood pressure. In Multivariate analysis age (AOR= 2.25), fast food intake (AOR= 1.50), Alcohol consumption (OR= 2.23), less physical activity (AOR=1.71), increased body mass index (AOR=2.42) remains significant predictor. Conclusion: Detecting the risk factors of high blood pressure prevalent in the population is of utmost importance to achieve a healthy population. Formulation and dissemination of need--based, culturally acceptable and age appropriate scientific messages for school students should be conducted more proactively. Keywords: Adolescents, Blood pressure, Risk factor, Rural school.

scholarly journals Assessment of Risk Factors for Overweight and Obesity: A Cross-Sectional Study among Rural School Going Children in Hooghly District, West Bengal

2021 ◽  
Vol 8 (11) ◽  
pp. 198-204
Author(s):  
Malay Kumar Das ◽  
Aparajita Dasgupta ◽  
Rabindranath Sinha
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Food Intake ◽  
Body Mass ◽  
High Blood Pressure ◽  
Fast Food ◽  
Overweight And Obesity ◽  
Non Communicable Diseases

Introduction: Intermediate school children are in the transition phase from adolescent to adulthood. This age group is known for experimentation and vulnerability to adopt lifestyles predisposing to non-communicable diseases. Method: A pre-designed and pre-tested questionnaire was used in class-room setting to collect information from students regarding presence of risk factors of non-communicable diseases. The respondents were also subjected to anthropometric measurements and blood pressure examination using standard operating procedures. Results: A total of 761 students of class VI-XII participated in the study of which 61.4% were boys and rests were girls. Increased body mass index among boys and girls were 12.6% and 11.6% were respectively. In Bivariate analysis fast food intake (>3 times/week) (OR=1.92), less physical activity (OR=1.86), high blood pressure (OR=2.53) were significantly associated with increased body mass index. In Multivariate analysis fast food intake (AOR=1.83), less physical activity (AOR= 1.94), high blood pressure (AOR=2.40) remains significant predictor. Conclusion: Therefore it is strongly felt that all efforts must be made to obviate the risk factors of overweight and obesity among the general mass at a very early age. Those efforts must be well structured, scientifically systematized and socially implementable. Keywords: Children, BMI, Risk factor, Rural school.

scholarly journals Risk factors mediating the effect of body-mass index and waist-to-hip ratio on cardiovascular outcomes: Mendelian randomization analysis

2020 ◽  
Author(s):  
Dipender Gill ◽  
Verena Zuber ◽  
Jesse Dawson ◽  
Jonathan Pearson-Stuttard ◽  
Alice R Carter ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Body Mass ◽  
European Ancestry ◽  
Standard Deviation Increase ◽  
Waist To Hip Ratio ◽  
Increased Risk ◽  
Artery Disease

Background: Higher body-mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits and smoking is not fully understood. Methods: Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, MR mediation analysis was performed to investigate the degree to which genetically predicted systolic blood pressure (SBP), diabetes, lipid traits and smoking mediated an effect of genetically predicted BMI and WHR on risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke. Results: The 49% (95% confidence interval [CI] 39%-60%) increased risk of CAD conferred per 1-standard deviation increase in genetically predicted BMI attenuated to 34% (95% CI 24%-45%) after adjusting for genetically predicted SBP, to 27% (95% CI 17%-37%) after adjusting for genetically predicted diabetes, to 47% (95% CI 36%-59%) after adjusting for genetically predicted lipids, and to 46% (95% CI 34%-58%) after adjusting for genetically predicted smoking. Adjusting for all the mediators together, the increased risk attenuated to 14% (95% CI 4%-26%). A similar pattern of attenuation was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcomes. Conclusions: Measures to reduce obesity will lower risk of cardiovascular disease primarily by impacting on downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.

scholarly journals Relation Between Preclinical Atherosclerosis and Venous Thromboembolism in Patients With Thrombophilias – Longitudinal Study

2014 ◽  
pp. S403-S409 ◽  
Author(s):  
O. AUZKÝ ◽  
R. DEMBOVSKÁ ◽  
J. MRÁZKOVÁ ◽  
Š. NOVÁKOVÁ ◽  
L. PAGÁČOVÁ ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Longitudinal Study ◽  
Venous Thromboembolism ◽  
Waist Circumference ◽  
Systolic Blood Pressure ◽  
Body Mass ◽  
History Of ◽  
Preclinical Atherosclerosis

Preclinical atherosclerosis may represent a risk factor for venous thromboembolism (VTE). In longitudinal study we followed longitudinally 96 patients (32 men) with thrombophilias with (n=51) and without (n=45) history of VTE. In both groups we studied the changes of preclinical atherosclerosis at peripherally located arteries detected by ultrasound. In addition, we assessed changes in selected risk factors of atherosclerosis. During the mean follow-up of 56.0±7.62 months we did not find significant change in preclinical atherosclerosis defined as Belcaro score in either group (–3 % in the VTE group vs 0 % in non VTE group). Significant increase in body mass index (1.03±1.98 kg*m-2, resp. 1.21±1.67 kg*m-2, p<0.01) and non-significant increase in systolic blood pressure were detected in both groups. Waist circumference increased significantly only in patients without VTE (4.11±7.84 cm, p<0.05). No differences in changes of risk factors under study between both groups were detected. In summary, patients with thrombophilia and history of VTE showed no evidence of greater progression of atherosclerosis or increase in traditional risk factors of atherosclerosis than patients with thrombophilia without history of VTE. Unfavorable changes of body mass index, waist circumference and systolic blood pressure were detected in both groups during study period.

scholarly journals Cross-Sectional and Longitudinal Associations between Body Mass Index and Cardiometabolic Risk Factors in Adolescents in a Country of the African Region

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Tanica Lyngdoh ◽  
Bharathi Viswanathan ◽  
Edwin van Wijngaarden ◽  
Gary J. Myers ◽  
Pascal Bovet
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Young Adults ◽  
Body Mass ◽  
Weight Status ◽  
Cardiometabolic Risk ◽  
Linear Regression Analysis ◽  
Cardiometabolic Risk Factors ◽  
Cross Sectional

We assessed the association between several cardiometabolic risk factors (CRFs) (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, uric acid, and glucose) in 390 young adults aged 19-20 years in Seychelles (Indian Ocean, Africa) and body mass index (BMI) measured either at the same time (cross-sectional analysis) or at the age of 12–15 years (longitudinal analysis). BMI tracked markedly between age of 12–15 and age of 19-20. BMI was strongly associated with all considered CRFs in both cross-sectional and longitudinal analyses, with some exceptions. Comparing overweight participants with those having a BMI below the age-specific median, the odds ratios for high blood pressure were 5.4/4.7 (male/female) cross-sectionally and 2.5/3.9 longitudinally (P<0.05). Significant associations were also found for most other CRFs, with some exceptions. In linear regression analysis including both BMI at age of 12–15 and BMI at age of 19-20, only BMI at age of 19-20 remained significantly associated with most CRFs. We conclude that CRFs are predicted strongly by either current or past BMI levels in adolescents and young adults in this population. The observation that only current BMI remained associated with CRFs when including past and current levels together suggests that weight control at a later age may be effective in reducing CRFs in overweight children irrespective of past weight status.

Aerobic Capacity, Obesity, and Atherosclerotic Risk Factors in Male Adolescents

PEDIATRICS ◽  
1985 ◽  
Vol 75 (5) ◽  
pp. 813-818
Author(s):  
Raymond R. Fripp ◽  
James L. Hodgson ◽  
Peter O. Kwiterovich ◽  
John C. Werner ◽  
H. Gregg Schuler ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Regression Analysis ◽  
Body Mass ◽  
Linear Regression Analysis ◽  
Density Lipoprotein ◽  
Plasma Triglyceride ◽  
Lipoprotein Cholesterol ◽  
Atherosclerotic Risk Factors

Correlations between aerobic capacity, obesity, and atherosclerotic risk factors were evaluated in adolescents with low-to-moderate levels of physical fitness. Subjects with higher levels of fitness had a more favorable risk profile with decreased body mass index, lower systolic and diastolic blood pressure and plasma triglyceride levels, and higher plasma high-density lipoprotein-cholesterol levels. Simple linear regression analysis revealed an association between body mass index and blood pressure, plasma triglyceride and plasma highdensity lipoprotein-cholesterol. The level of aerobic fitness as determined by exercise duration was also associated with the same atherosclerotic risk factors. However, multiple linear regression analysis demonstrated that body mass index provided the largest explanation, by those variables examined, of the interindividual variance in blood pressure, plasma triglyceride, and high-density lipoprotein-cholesterol. Aerobic fitness contributed only minimally to the variation in these risk factors. These findings suggest that if aerobic conditioning is used to modify atherosclerotic risk factors, it should be accompanied by a reduction in weight in adolescents with low-to-moderate levels of physical fitness.

scholarly journals Association between eating habits, body mass index, cardiorespiratory fitness, and cardiometabolic risk factors in children

2021 ◽  
Vol 34 ◽  
Author(s):  
Miguel Angelo dos Santos DUARTE JUNIOR ◽  
Adroaldo Cezar Araujo GAYA ◽  
Vanilson Batista LEMES ◽  
Camila Felin FOCHESATTO ◽  
Caroline BRAND ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Body Mass ◽  
Cardiorespiratory Fitness ◽  
Cardiometabolic Risk ◽  
Eating Habits ◽  
Density Lipoprotein ◽  
The Body ◽  
Cardiometabolic Risk Factors

ABSTRACT Objective To verify the multivariate relationships between eating habits, cardiorespiratory fitness, body mass index, and cardiometabolic risk factors in children. Methods This is a cross-sectional study developed in a public elementary school with 60 first- to sixth-graders. Their eating habits were assessed using the Food Frequency Survey, weight, height, and cardiorespiratory fitness, assessed according to the Projeto Esporte Brasil protocol. Moreover, the variables, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, adiponectin, leptin, diastolic and systolic blood pressure were evaluated. Descriptive statistics were used for data analysis and generalized estimation equations were used for the analysis of direct and indirect relations, in a multivariate analysis model with several simultaneous outcomes. Results It appears that the eating habits and cardiorespiratory fitness explain 20% of the body mass index. Cardiometabolic risk factors are explained by the relationship between eating habits, cardiorespiratory fitness, and body mass index, according to the following percentages: 29% (systolic blood pressure), 18% (diastolic blood pressure), 63% (leptin), 4% (adiponectin), 14% (C-reactive protein), 17% (insulin), 10% (high-density lipoprotein), 1% (low-density lipoprotein), 4% (glucose). It is also observed that the effects of the eating habits on cardiometabolic risk factors are indirect, that is, they are dependent on changes in the body mass index and cardiorespiratory fitness levels. Conclusions The relationship between eating habits and cardiometabolic risk factors in children is dependent on cardiorespiratory fitness and body mass index. Thus, our findings suggest a multivariate relationship between these factors.

Sign in / Sign up

Export Citation Format

Share Document