ABSTRACT
Various anthropometric markers of adiposity such as body mass index (BMI), waist circumference (WC), neck circumference (NC), hip circumference (HC), waist-hip ratio (WHR), waist-height ratio (WHtR) and body adiposity index (BAI) have shown varying degree of correlation with the components of metabolic syndrome (MetS) among different sexes, races and ethnic groups. There are conflicting data from previous reports on the relationship between digit ratio(2D:4D) and adiposity markers. Data on relationship between 2D:4D and MetS are scarce. The aim of the study was to investigate the effects of body adiposity indices, 2D:4D and level of physical activity (PA) on metabolic syndrome components and biomarkers among Hausas of Kano, Nigeria. The study comprised of a total of 465 participants pooled from rural and urban communities comprising of 266 males and 199 females selected by systematic random sampling out of which blood samples of 161 subjects were used for serum analysis (male n = 120, female n = 41). Body mass index (BMI), waist circumference (WC), neck circumference (NC), hip circumference (HC), waist-hip ratio (WHR), waist-height ratio (WHtR), body adiposity index (BAI), digit length and 2D:4D were measured and calculated using standard protocols. Visceral adiposity was measured using sex specific visceral adiposity index (VAI). After at least 8 hours of fasting, venous blood samples were drawn for estimation of glucose, high density lipo-protein cholesterol (HDL–C), low density lipo-protein cholesterol (LDL–C), total cholesterol (TC), triglyceride (TG), uric acid (UA) and adiponectin using standard laboratory protocols. Physical activity levels were assesed using self reported PA questionnaire. Chi-square test, independent sample t-test, Pearson‟s correlation, multiple
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and binary logistic regression, receiver operating characteristic curve were used as statistical tools. P < 0.05 was set as the level of significance. The results show that 2D:4D and all the indices of adiposity with exception of BAI, WC and BMI are sexually dimorphic. 2D:4D, HC, WHtR and VAI were higher in females than in males whereas, WHR, NC were higher in males. TC, HDL-Cand fasting blood glucose (FBG) were significantly higher in females (P< 0.05). TG, LDL, SUA, adiponectin and blood pressure (BP) showed no significant sex difference. 2D:4D, all the indices of body adiposity and BP were significantly higher in urban participants (P < 0.05). While adiponectin and HDL were significantly higher (P < 0.05) in rural subjects, all other serum parameters were higher in urban participants (P < 0.05). Effect of urbanization was higher on central indices (P < 0.05) and in females (P < 0.05). 2D:4D, VAI and other adiposity indices correlated positively with serum uric acid (SUA) and serum components of MetS but negatively with HDL and adiponectin. VAI was superior to all the anthropometric indices. WHR was the best anthropometric predictor of MetS [example for LDL-C = 361.12 (WHR) + ( -215.15) in males and LDL-C = 472.19 (WHR) + ( -308.21) in females]. BAI, NC and HC were weak predictors. Compared to L2D:4D, R2D:4D was a stronger MetS correlate (with adiponectin, L2D:4D and R2D:4D correlation coefficients were -0.572 and – 0.634 respectively, P < 0.001). Adiposity measures and MetS components decreased significantly (P < 0.05) with increased PA level. The effects of moderate and optimal PA levels on most adiposity and metabolic indices showed no significant difference (P > 0.05). 2D:4D correlated inversely with PA levels. MetS components were predicted from anthropometric measures of adiposity, digit length and digit ratio with WHR having the highest percentage contribution (for LDL, 67% in males and 82% in females). Cut off values of adiposity
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measures for MetS components were mostly higher in males than in females and slightly different from those reported for other races. It is conluded that 2D:4D is a positive correlate of body adiposity and MetS, a possible marker of physical activity behaviour and that WHR is the best anthropometric predictor of MetS while VAI is superior to simple anthrpometric measure for MetS prediction in Hausas of Kano. Also, urbanization adversely affects body adiposity and MetS, while PA lowers adiposity and MetS measures.
TABLE OF CONTENTS
Cover Page ……………………………………………………………………………………………………….. i
Title Page ………………………………………………………………………………………………………… ii
Declaration …………………………………………………………………………………………………….. iii
Dedication ………………………………………………………………………………………………………. v
Acknowledgements ………………………………………………………………………………………….. vi
Table of Contents …………………………………………………………………………………………… viii
List of Tables ………………………………………………………………………………………………….. xi
List of Figures ……………………………………………………………………………………………….. xiii
List of Plates ………………………………………………………………………………………………….. xv
List of Appendices………………………………………………………………………………………….. xvi
List of Abreviations ……………………………………………………………………………………….. xvii
Abstract ………………………………………………………………………………………………………. xxii
1.0 INTRODUCTION ……………………………………………………………………………………… 1
1.1 Background of the Study……………………………………………………………………………….. 1
1.2 Statement of Research Problem …………………………………………………………………… 9
1.3 Justification/Significance of the Study ………………………………………………………… 10
1.4 Aim And Objectives of the Study ……………………………………………………………….. 12
1.5 Research Questions …………………………………………………………………………………… 13
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2.0 LITERATURE REVIEW ………………………………………………………………………….. 14
2.1 Molecular and Genetic Basis of Body Adiposity ………………………………………….. 14
2.2 Visceral Adiposity …………………………………………………………………………………….. 20
2.3 Digit Length and Digit Ratio ……………………………………………………………………… 37
2.4 Metabolic Syndrome……………………………………………………………………………………..41
2.5 Anthropometric and Visceral Adiposity Indices ………………………………………….. 44
2.6 Anthropometric Cut Off Values For Metabolic Syndrome In Some Ethnic Group………………………………………………………………………………………………………………..63
3.0 MATERIALS AND METHODS……………………………………………………………………667
3.1 Study Area ………………………………………………………………………………………………. 67
3.2 Study Site ……………………………………………………………………………………………….. 69
3.4 Sampling Technique …………………………………………………………………………………. 72
3.5 Ethical Approval ………………………………………………………………………………………. 72
3.6 Equipment and Instrument ……………………………………………………………………….. 72
3.7 Reagents ………………………………………………………………………………………………….. 74
3.8 Methods …………………………………………………………………………………………………… 75
3.9 Measurement of Blood Pressure ……………………………………………………………….. 82
3.10 Visceral Adiposity Estimation Using Sex Specific Visceral Adiposity Index….. 83
3.11 Assessment of Levels of Physical Activity ………………………………………………….. 84
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3.12 Blood Collection and Processing ………………………………………………………………. 84
3.13 Laboratory Analytical Methods ……………………………………………………………….. 85
3.14 Statistical Analyses …………………………………………………………………………………. 93
4.0 RESULTS ……………………………………………………………………………………………….. 95
5.0 DISCUSSION ………………………………………………………………………………………… 153
6.0 CONCLUSION AND RECOMMENDATIONS ………………………………………… 180
6.1 Conclusion ……………………………………………………………………………………………… 180
6.2. Recommendations ………………………………………………………………………………….. 182
6.3 Contribution to Knowledge …………………………………………………………………….. 183
REFERENCES ……………………………………………………………………………………………. 186
APPENDIX………………………………………………………………………………………………………230
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Study
Various anthropometric markers of adiposity (body mass index, waist circumference, neck circumference, hip circumference, waist-hip ratio, waist-height ratio, body adiposity index) have shown varying degrees of correlation with the components of metabolic syndrome among different sexes, races and ethnic groups (Akuyam et al., 2009; Anyanwu et al., 2011; Zhang et al., 2013a,b), suggesting that there are gray areas to be unraveled about the determinants and factors that affect this relationship. The cut off values of anthropometric measurements that predict metabolic syndrome have been redefined based on races and/or ethnicity. For example, the Asians and Europeans have stipulated the cut off values for the indices of truncal adiposity (WC, HC and WHR) and BMI based on the peculiarity of the relationships between the components of metabolic syndrome and critical measures of adiposity markers in their population (Tulloch-Reid et al., 2003). Enviromental factors specific to certain populations such as urbanization have been shown to affect obesity and its relationship with some components of the metabolic syndrome (Ekezie et al., 2011).
Blacks are known to have lower body fat for the same anthropometric adiposity measure than Caucasians and since the interrelationships between the adiposity markers and metabolic syndrome is tightly tied to their ability to quantify body fat, this has implications on the relationship between adiposity markers and the components of the metabolic syndrome (Deurenberg et al., 1998). The close association between either absolute total fat or adipose tissue distribution and metabolic syndrome has been well documented (Wajchenberg, 2000). Nevertheless, controversy remains over which anthropometric
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parameter best defines obesity and conveys the highest risk of cardiometabolic disturbance and the uniform applicability of these markers across populations of different races and ethnicity. In recent years, waist-to-height ratio (WHtR) has been regarded as the best screening tool for detecting cardiometabolic risk factors, especially in Asians (Lin et al., 2002; Hsieh et al., 2003; Shao et al., 2010). Some studies in other populations have proposed the use of waist circumference (WC) or waist-to-hip ratio (WHR) (Ho et al., 2003; Esmaillzadeh et al., 2004), whereas others advocate their combined use (Al-Odat et al., 2012; Feng et al., 2012). Although BMI, WHtR, WC and WHR are simple and convenient measures for epidemiological studies, their validity in measuring adiposity has been questioned because they do not directly measure the amount of visceral adipose tissue and cannot differentiate between fat and lean mass (Wannamethee et al., 2005). The notion that BMI and other simple anthropometric measurements may not fully define metabolic risk has led to increased attention on other distinct aspects of adiposiy (Kramer et al., 2013). Visceral adiposity has been suggested as a complementary risk factor, given its pathogenic consequences in animal models and the significant epidemiologic data suggesting its role in metabolic dysfunction (Bays, 2011). In animal models of obesity, dysfunctional visceral adipocytes represent a locus of inflammation and insulin resistance (Samaras et al., 2010; Kabir et al., 2011). Indeed, in humans, an improvement in insulin sensitivity is associated with changes in visceral fat (Borel et al., 2012) and inflammation within visceral adipose tissue is associated with systemic insulin resistance, inflammation and endothelial dysfunction (Farb et al., 2011).
Visceral fat has been associated with cardiovascular events (Britton et al., 2013), left ventricular remodeling (Neeland et al., 2013) and dysglycaemia (Kanai et al., 1996; Fox et
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al., 2007; Liu et al., 2010) in multiple large, community-based cohort study. Although it has been suggested that a direct estimation of visceral adiposity would have higher value in predicting obesity-related health risks (Borruel et al., 2014), previous studies in multiethnic population have produced inconsistent findings. Some studies have found that direct visceral adiposity indictors exhibited better predictive performance than simple anthropometric parameters (Muller et al., 2012) and others have found them to be equivalent (Mueller et al., 1991; Marno et al., 2008; Mbanya et al., 2015). However, some studies have observed the discriminatory capability of the simpler measures to be more robust for some metabolic parameters (Ike et al., 2000;Smith and Haslam,2007). Visceral adiposity, the amount of visceral fat deposit in the body, is documented to have a strong relationship with serum lipid profile, glycaemic level and blood pressure and thus, a major step in the pathogenesis of metabolic syndrome (hyperlipidaemia, hyperglycaemia and hypertension) (Ike et al., 2000). Visceral adipose tissue is a pro-inflammatory endocrine tissue and may account for an increased cardiometabolic risk across BMI as seen in certain populations (Bays, 2011).
A recent report in obese individuals of European ancestry demonstrated that a single measurement of visceral fat (VF) was associated with risk of dysglycaemia, dislipidaemia and hypertension independent of weight or other anthropometric indices, suggesting that visceral adiposity could be a hallmark of metabolically obese phenotype regardless of other adiposity status and may serve as a marker and target of therapy in cardiometabolic diseases (Bays, 2011). Also comparative evaluation of body composition of Nigerians by bioimpedance analysis showed that individuals with type 2 diabetses mellitus (DM) have
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significantly higher total body and visceral fat than age and sex-matched counterparts (Owolabi et al., 2016). There is controversy regarding the specific mechanisms by which fat in the visceral compartment confers greater risk than subcutaneous fat (Kissebah and Peiris, 1989; Kraegen et al.,1991). Some investigators have suggested that one or more moieties secreted by the visceral adipocyte might mediate insulin resistance and thus, metabolic syndrome. Among the mediators are free fatty acids (FFAs) and adipose tissue–released cytokines (adipokines) such as interleukin-1, interleukin-6, tumor necrosis factor – resistin or a reduction in adiponectin (Kissebah and Peiris, 1989). Also that the anatomical position of the visceral adipose depot (that is., portal drainage into the liver) plays an important role in the pathogenesis of the MetS (Kraegen et al., 1991). In recent years, visceral fat has emerged as an important measure of cardiometabolic risk. Although magnetic resonance imaging (MRI) and computed tomography (CT) scan can estimate the degree of visceral fat, these methods are not feasible in the routine clinical setting (Borruel et al., 2014). The gold standard assessment method for the estimation of visceral fat content has been MRI and CT scan. However, these methods are not pragmatic owing to the cost and time involved in their utilization (Borruel et al., 2014). Visceral adiposity which is mainly aggregation of unwanted fats in the abdominal region is known to rise steadily as age advances in both genders.
Visceral adiposity index (VAI) is a recently derived index to measure visceral fat based on the knowledge of waist circumference (WC), plasma HDL, triglycerides and BMI. The
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visceral adiposity index has been adjusted for gender and is based on the formula proposed by Amato and Giordano (2014). The recent development of this sex-specific mathematical model –VAI provides a simple means by which the quantity of visceral fat can be estimated and since it is even shown that VAI was highly correlated with body visceral adiposity measured by sophisticated methods such as MRI and CT scan, the indication for its use is strengthened. Consequently, the index is presumed to be a more reliable predictor of MetS than simple anthropometric measures (Zhang et al., 2013b). While this theory is upheld by the findings of some researchers (Al-Daghri et al., 2013; Li et al., 2013), others maintain that simple anthropometric measures demonstrates better relationship with certain components of the MetS in some populations (Bozorgmanesh et al., 2011; Ciresi et al., 2012). These conflicting opinions may suggest that in addition to the insulin resistance theory associated with visceral adiposity, there are probably other complex pathophysiological mechanisms linking body adiposity with MetS and the ethnic and racial discrepancy in this relationships further suggest ethnic predilections in the aetiopathogenesis.
Adiponectin (also known as: ACRP30, apM1, adipoQ and GBP28) is a hormone produced exclusively by the adipocyte. Initial identification of this protein was made in 1995 through the isolation of a cDNA using a subtractive hybridization screen designed to identify genes up-regulated during adipocyte differentiation (Scherer et al., 1995). Adiponectin is dramatically up-regulated during adipogenesis and remains one of the most adipocyte specific gene products identified to date. Adiponectin consists of an amino-terminal signal sequence, a variable region and a collagenous domain (Pajvani et al., 2003). Adiponectin functions as an insulin sensitizer by decreasing hepatic glucose output and thereby
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contributing to the regulation of whole-body glucose homeostasis. It prevents insulin resistance, a major step in the pathogenesis of metabolic syndrome, thus, making its serum level to correlate negatively with the components of the syndrome (Stefan et al, 2003). Although there are slight ethnic variations in the serum levels of adiponectin, it is generally agreed to correlate negatively with MetS regardless of age and ethnicity (Hu et al.,1996; Hotta et al., 2000; Weyer et al., 2001; Hotta et al., 2001 and Stefan et al., 2002). The sex difference in thepattern of body fat distribution is explainable by fat distribution effect of the sex hormones, in that while oestrogen encourages fat deposition in the thigh and buttocks, testosterone enhances fat deposition in the abdomen (Lemieux et al., 1993). The study of finger lengths and especially the ratio of second to fourth digit (2D:4D) has received great attention (Manning et al., 1998; Putz et al., 2004; Hone and McCullough, 2012; Manning et al., 2014).
Transmitted through genetic inheritance and later unchanging, the ratio of 2nd and 4th fingers (2D:4D) is related to prenatal exposure to testosterone (Umut et al., 2015). Studies on the genetics of obesity performed on twins, suggests that the BMI, an indicator of generalized obesity may be transmitted through genetic inheritance (Sengier, 2005). Another anthropometric measure transmitted by genetic inheritance is finger length ratio as research has found that from the moment these are determined in the mother‟s womb during the 13th-14th week of intra-uterine life (Van Anders and Hampson, 2005), this does not change either in the adolescent period or in adulthood (Çelik et al., 2010). There are studies reporting that 2D:4D on the hand is related to the level of sex hormones in the body (Manning et al., 1998; Manning et al., 2001) . Accordingly, there is a relationship between index finger length and the level of the estrogen in the female gender and a relationship
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between ring finger length and the level of the hormone testosterone in the male gender (Manning et al., 2001). Sequel to above, it can be deduced that 2D:4D of the hand is hormonally and genetically determined. Since there are also evidences to suggest that body fat distribution pattern is determined by sex hormones and are also genetically predisposed (Lemieux et al., 1993) it is possible that 2D:4D may be related to the adiposity markers, its metabolic consequences and serum biomarkers since 2D:4D ratio has been reported to correlate positively with traits putatively linked to testosterone (Benderlioglu and Nelson, 2004; Van Anders and Hampson, 2005; Muller et al., 2011; Kangassalo et al., 2011). Indeed it has been demonstrated that 2D:4D positively correlates with BMI (Danborno et al., 2008; Umut et al., 2015) negatively with muscle mass (Umut et al., 2015), positively with waist-to-hip ratio (Oyeyemi et al., 2014). Also its significant relationship with chest, waist and hip circumferences has also been documented (Danborno et al., 2008). Low levels of physical activity are associated with a high prevalence of MetS (Guinhouya et al., 2011). The inverse relationship between physical activity levels and the prevalence of metabolic risk factors independent of age, gender, BMI and adiposity is well documented (Andersen, 2006; Butte et al., 2007).
Physical activity is known to be protective against adiposity and its metabolic consequence. The indicators of generalized adiposity (BMI) and truncal adiposity (WC, HC, WHR, WHtR, BAI, NC) have been shown to correlate negatively with level of physical activity and so are the components of MetS (Guinhouya et al., 2011). The various components of the metabolic syndrome are modulated to different extent and by different mechanisms by
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physical activity levels (Dietz, 1997). Exercise increases insulin sensitivity both acutely and chronically (Henriksen, 2002). Acute exercise is characterized by changes in insulin signaling in response to muscle contraction (Henriksen, 2002). There is an increased translocation of glucose transporter type 4 (GLUT4) to the cell surface and GLUT4 are found in adipose tissues and striated muscle and are responsible for insulin-related glucose uptake and storage (Ren et al., 1994). Physical activity (PA) increases GLUT4 content, glycogen synthase activity, mitochondrial enzyme activity and density in skeletal muscle (Holloszy, 2005; Eisenmann et al., 2007; Venables and Jeukendrup, 2008). However, some evidences exist to suggest that there is gender discrepancy in PA induced insulin sensitivity, in that females respond better than males for age matched counterparts following the same dose and duration of aerobic PA (Lee, 2012). The acute effect of aerobic exercise can last up to 48 hours, which provides a rationale for recommendations to exercise regularly (Venables and Jeukendrup, 2008). The blood pressure lowering effect of aerobic physical activity has been reported by many researchers (Meyer et al., 2006; Tjønna, 2009; Ben Ounis, 2010) but there seem to be some inconsistency on the findings concerning the extent to which exercise lowers blood pressure and which component of the blood pressure is more affected. While some studies revealed significant reduction in both systolic and diastolic blood pressure (Meyer et al., 2006; Tjønna, 2009), others revealed signicant reduction only in the systolic blood pressure (Naylor, 2008).
Abnormal serum lipid profile is associated with a poor quality diet rich in fat. A balanced diet, low in saturated fat, aiming to reduce triglyceride concentrations and TC as well as increase HDL-C concentration is usually the first line of treatment. However, the varying
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effects of exercise on blood lipids have been investigated. Serum cholesterol, TG, LDL-C and HDL-C are reported to respond differently to aerobic exercise by different studies (Kelly, 2004; Meyer et al., 2006; Lee et al., 2010) Overall, a negative and dose- related relationship exists between physical activity and most MetS parameters despite using a wide range of participants, sample sizes and exercise programmes that differed in intensity, duration, modality and setting. This relationship appears to be either independent of other factors or alternatively, simultaneously mediated by the physical fitness and adiposity of the participants (Guinhouya et al., 2011).
1.2 Statement of Research Problem
MetS is one of the leading causes of morbidity and mortality both in developed and developing countries. Despite the ongoing global efforts at determining ethnic specific anthropometric predictors and cut-off values for the syndrome, such data are lacking in Nigeria and among the Hausa ethnic group. Prediction of MetS by anthropometric studies had focused mainly on using BMI and more recently the indices of truncal obesity (WC, NC, WHR, WHtR, HC) with varying and sometimes contrasting predictive powers for the different components of the syndrome The usefulness of sex-specific visceral adiposity index and its possible superiority over the simple anthropometric parameters has not been well documented in Nigeria, with particular paucity of such data among the Hausa ethnic group. Furthermore, correlating the various anthropometric markers of adiposity with specific components of the MetS and its serum biomarkers have received less attention in the literature. Additionally, 2D:4D like body fat distribution, is an anthropometric variable that is hormonally and genetically determined. Conflicting data from previous researches on the relationship between 2D:4D and adiposity markers suggests that although genetic
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constitution and sex hormones are crucial to both, there are probably other factors that affect this relationship which needs to be further explored. Moreover, most of the studies made little attempt to determine and quantify sexual dimorphism in this relationship. Also correlating this important variable with the components of MetS and its serum biomarkers has received little attention. Although the inverse relationship between physical activity levels with MetS parameters and adiposity indices is well documented, studies comparing the impact of the various levels of physical activity on the different measures of adiposity and individual components of MetS is scarce in Nigeria and especially among the Hausa ethnic group.
1.3 Justification of the Study
The availability of population specific anthropometic predictors of the various components of MetS in some parts of the world and the paucity of such data in Nigeria and particularly among the Hausas may provide a justification for this work. Also the establishment of a relationship between the visceral adiposity index and anthropometric markers of adiposity with serum triglyceride, low density lipoprotein cholesterol, high density lipoprotein cholesterol, glucose and systemic blood pressure and comparing the sensitivity and specificity of each for these components of MetS are justified.
Following the recent declaration of the World Health Organisation that obesity is assuming an epidemic and pandemic dimension and the emphasis on its tight association with MetS which is a leading cause of morbidity and mortality worldwide, it is important to identify germane population specific adiposity markers for the components of MetS. Establishing a direct relationship between digit ratio and the various metabolic consequences of adiposity (dislipidaemia, disglycaemia and hypertension) is particularly an interesting idea as it opens
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another window of opportunity for predicting MetS from a simple anthropometric measurement. Since the different measures of body adiposity (truncal, generalized and visceral) do not pose equal metabolic risk, it is therefore justified to quantify the impact of various levels of physical activity on the adiposity indices and their metabolic consequences. The variability and discriminatory strength of the anthropometric markers of adiposity in predicting or identifying the MetS phenotype is of immense clinical significance. The study may provide effective and cheap initial screening criteria for individuals susceptible to MetS especially in a large scale epidemiological survey where invasive procedures are relatively more expensive and often not feasible. The idea is to ensure early diagnosis and commence early treatment in view of halting disease progression and preventing complications. The various components of MetS are associated with specific but interrelated complications. Consequently, establishment of a relationship between anthropometric indices and each component will be interesting and certainly an improvement of the current status of knowledge. Moreover, comparing the visceral adiposity index with the simple anthropometric indices will be useful in identifying the merits and demerits of each in the Hausa population.
Additionally, finding the Hausa ethnic specific cut-off values of the various anthropometric measures of adiposity for the different MetS components and using serum adiponectin and uric acid as biomarkers to validate the relationship of the adiposity indices with MetS parameters will certainly add value to the biochemical and clinical evaluation of the MetS. Furthermore, finding the relationship between digit ratio with body adiposity indices, MetS and its serum biomarkers may provide yet another simple anthropometric variable for
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initial screening of individuals susceptible to MetS especially among the Hausa population where exposure of certain body parts such as waist, hip and neck for anthropometric studies may not be convenient for female subjects due to cultural factors, especially during a large scale epidemiological survey where ensuring privacy for every subject may not be practically feasible. In addition, quantifying the relationship between mild, moderate and rigorous physical activity with different adiposity measures and various MetS parameters may serve as the basis for recommendation of therapeutic exercise regimen for the different obesity phenotypes and for individuals with obesity related metabolic disorders.
1.4 Aim and Objectives of the Study
1.4.1 Aim of the Study To determine the effects of body adiposity indices, digit ratio and level of physical activity on MetS and serum biomarkers among the Hausas of Kano State. 1.4.2 Objectives of the study The objectives of the study were to:
i. determine sexual dimorphism in the visceral and anthropometric adiposity markers, digit ratio and MetS parameters,
ii. investigate the comparative effect of urbanization on digit ratio, different body adiposity measures, component of metabolic syndrome, serum uric acid and adiponectin,
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iii. find the relationship between anthropometric and visceral adiposity indices with metabolic syndrome components, serum adiponectin and uric acid,
iv. compare the effect of physical activity and urbanization on different measures of body adiposity, digit ratio and components of MetS,
v. find the correlation of digit ratio with visceral and anthropometric adiposity indices,
vi. find the relationship between digit ratio with MetS parameters, uric acid, adiponectin,
vii. formulate a linear regression equation for predicting the components of the MetS from anthropometric indices and digit ratio,
viii. determine the cut-off values of the anthropometric measures of adiposity for each component of the MetS.
1.5 Research Questions
i. The different body adiposity measures are not equally associated with the components of MetS. ii. Visceral adiposity index is superior to simple anthropometric measurement in its relationship with components of MetS. iii. Digit ratio ratio has a strong relationship with body adiposity and MetS. iv. Physical activity has different impact on the body adiposity measures and MetS components.
v. Urbanization has varying adverse effects on body adiposity and MetS indices.
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