Chronic Kidney Disease: Body Mass Index and Haemoglobin

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Chapter one: Introduction

Introduction and Background Information

Across the globe, chronic kidney disease (CKD) is categorised as a critical health problem. It is defined as glomerular filtration rate (GFR)<60Ml/min/1.73m² for >3 months irrespective of diagnosis, or kidney damage. The damage to the kidney is identified by abnormalities in the patients’ blood or urine. It is also identified through imaging tests kidney biopsy.

The prevalence of CKD is on the rise. It has reached pandemic levels across the globe.¹ Chronic Kidney Disease affects approximately 7-10% of the adult population in the UK. According to the World Health Organisation, kidney disease leads to 850,000 deaths in the world annually. It also accounts for 15,010,167 in disability-adjusted life years. The consequences of the disease among children are far more devastating because it condemns the child to various levels of lifelong medical disabilities.

The dominant causes of CKD among adults are hypertension and diabetic nephropathy. However, irrespective of the factors that initiate the condition, the onset of the disease triggers a chain of occurrences. The events predictably describe a common final pathway where the condition progresses to kidney failure. It is observed that the condition is associated with increased risk to cardio-vascular disease, stroke, renal failure, and death.

The increase in the prevalence of CKD is attributed to different factors. For instance, various studies that have been undertaken to determine the various conditions associated with CKD have pointed out to the possible relationship between the disease, levels of haemoglobin concentration, and obesity.² However, the findings have elicited debates, which have necessitated more epidemiological studies in the endeavour to conclusively establish the associations between obesity and haemoglobin levels among people with CKD.³ Even though there is a marked progress in the studies, there are arguments purporting that the relationships may vary based on different factors.

The current study was conducted against this background. The findings of the research will expand the knowledge regarding the relationship between BMI and haemoglobin among patients with CKD. The findings of the study will inform policy development.

Overweight and Obesity

Obesity and overweight have been on the rise. They have attained such global proportions as to be categorised as epidemics. Epidemiologists suggest that the two conditions can lead to the impairment of kidney functions.⁴ However, most studies carried out in relation to overweight and obesity are inconclusive. Nevertheless, some studies have pointed out to the existence of positive relationship between BMI and CKD. For instance, some researchers have tried to show that people with high BMI baseline have a high probability of future renal dysfunction.

Some studies indicate that there are different pathways in which weight may contribute to renal diseases. Some of the pathways include lipid disturbances, pro-inflammatory states, as well as hormonal and hemodynamic factors.⁵ The studies that point out to these pathways are established in general populations. However, it is worth noting that the researches are conflicting. As such, it is difficult to provide comparisons bearing in mind that different markers are used to quantify obesity. The markers include race and socio-economic factors. The variations highlight the need for specific studies to investigate the implications of BMI among people with CKD.

Haemoglobin

Concentration of haemoglobin indicates the presence of anaemia. Anaemia is common among patients suffering from CKD, which is a pointer to the crucial function that kidneys play in haemopoisesis, oxygenation, and stimulation of the precursors for haemopoietic in the bone marrow.⁶ Based on this perspective, the level of haemoglobin among people suffering from CKD oscillates above or below the recommended targets within short periods. As a result, anaemia develops as a possible complication associated with CKD.

Some studies indicate that the fluctuation of haemoglobin is associated with the severity of the renal dysfunction.⁷ The correlation between the renal function and the haemoglobin levels is the basis on which Erythropoietin-stimulating agents (ESA) are used in the management of CKD. It is, however, important to note that there are multifactor causes of anaemia. For instance, it may be caused by lack of iron in the diet, folate, vitamin B12, and Erythropoietin.⁸ In the case of CKD, the most significant cause of anaemia is Erythropoietin deficiency.

It is worth emphasising that CKD has become a global health problem whose prevalence has been on the rise both in the developed and developing nations. With the increase in obesity and cases of anaemia around the world, the two conditions can be categorised as major co-morbidities of CKD patients. The co-morbidity of anaemia gets more pronounced at the later stages of the kidney complications.⁹

Based on the varying evidence about BMI and haemoglobin implications in CKD, it is apparent that there is a need for a conclusive study to determine the relationship that exist and its impacts on the management of the condition. The recognition of the manifestation of the co-morbidities of CKD is a major milestone in the formulation of policies regarding the treatment and management of renal complications.

Objectives of the Study

The objective of the study was to establish the relationship between obesity, its subsequent influence on anaemia, and the effects of anaemia on CKD. Many studies have been carried out to enhance the understanding of CKD and to inform the design of possible intervention programs for both prevention and management of the condition.

However, the existing awareness of the causes of CKD is low among the healthcare policy formulators, caregivers, and the patients.¹⁰ As such, there is a need for the creation of adequate awareness about CKD and the multi-factorial causes associated with it. For instance, it is important to establish the relationship between haemoglobin levels and the BMI of patients with diabetes mellitus, which, according to researchers, is one of the major causes of kidney diseases. Such knowledge is critical in guiding the policy development and the implementation of intervention programs.¹¹

To this end, the major objective of the current study was to evaluate the relationship between BMI and haemoglobin in a population with CKD. The objective will guide the collection of data that can be used to inform development of policies on the prevention and management of CKD.

Implications for Policy

The 21st century has witnessed an increased emphasis on the implementation of healthcare policies that are evidence-based. The move has created the need for health researchers to invest in studies aimed at understanding the various complications associated with CKD and how they can be managed to increase the quality of life for the patients.

Despite the many studies undertaken, the findings regarding the relationship between haemoglobin, BMI, and CKD are inconclusive. Some of the factors that have aggravated the nature of the inconclusive findings are variations based on gender, race, and socio-economic factors. The differences have been identified both in cross-sectional and longitudinal studies investigating the association between BMI and haemoglobin. For example, there is evidence of variations in the nutritional status of different populations, which may affect the BMI of the individuals.

In relation to haemoglobin levels, studies have shown that patients with defective kidneys, and who are put under human Erythropoietin treatment, reflect poor response to the drug.¹² The poor response is brought about by the association between the condition and iron deficiency.¹³ The implication is that if the iron deficiency is corrected, response to therapy will be considerably increased as proper haemoglobin levels are restored. Similarly, some studies investigating the relationship between BMI and CKD have found that the prevalence of the condition is higher among people with high BMI. However, there are variations between men and women, especially among patients with diabetes and hypertension. To this end, women register high BMI compared to men.¹⁴

To improve cost effectiveness in the treatment of CKD, there is a need to have an in-depth understanding of the main co-morbidities associated with the condition. In addition, the establishment of the relationship between the co-morbidities presents the health providers with a basis for policy formulation, which ensures that therapists take into consideration the management of these elements. The studies should be patient-based as opposed to blanket application, which may render the policies ineffective. Such policies lead to inadequate treatments, which may later result in complications. The common problems include the progression of the condition to the final stages of renal dysfunction, cardiovascular complications, and poor quality of life for the patients.¹⁵

The general rationale for the screening of a medical condition is that the problem is sufficiently prevalent and has an association with adverse impacts as to be of significant public health concern. The condition should also be detectable in early clinical stages. In addition, the treatment should improve health outcomes. The screening for eGFR among obese people offers an opportunity for nationwide attention and intervention through sensitisation campaigns aimed at educating the general population on the risks of anemia and CKD. Consequently, the findings of the current study will inform the policymakers on the need for awareness campaigns and other systems, which act as mitigating factors in addressing the escalating problem of CKD among the population.

It is important for the policymakers and the health providers to understand the factors that aggravate the CKD in specific populations. Bearing this in mind, the following study provides an analysis of the relationship between BMI and haemoglobin in ICLDC population corrected for CKD. The study will provide important information for the formulation of policies for the management of the patients.

Rationale

It has been established that some of the debilitating conditions among patients with CKD include anaemia and obesity. Consequently, comprehensive awareness regarding the complications can enhance the quality of care accorded to the patients. It is worth noting that the high prevalence of obesity among women does not rule out the co-morbidity of this condition among the men with renal dysfunction. In fact a study conducted by the Obesity and Renal Cancer Association found that the risk of renal cell cancer was high among both men and women.¹⁶

In relation to anaemia, it has been found that people with CKD can suffer from anaemia due to different reasons. As such, in the treatment process, there is the need to carry out an in-depth analysis to establish the main causes of the complication. Anaemia occurs before the decline in renal function due to Erythropoietin deficiency. It is important to note that Erythropoietin has anti-inflammatory and anti-obesity effects. Consequently, an inflammation may have an implication on Erythropoietin. It has also been noted that there are other factors during inflammation that affect Erythropoietin.

They include, among others, Hepcidin. It must be understood that Erythropoietin deficiency is a major cause of anaemia among CKD patients. As such, the treatment of CKD should be preceded by the evaluation of the BMI status and the causes of the anaemia in the patient, which is followed by appropriate management. In addition, there should be a clear understanding of the association between BMI and haemoglobin. The understanding will help to avoid the use of CKD therapies that are rendered ineffective by the obesity and anaemia conditions.

Bearing in mind the implications of high BMI and anaemia, it is important to carry out an in-depth analysis to describe the association between the former and haemoglobin in populations with CKD. The information will be paramount in the formulation of health policies. In addition, it will help in the compilation of the right treatment and reduction of the morbidities and mortalities among populations with renal complications. The current health policies, however, do not take into account the association between BMI and anaemia.

Definition of Terms

Stages of Chronic Kidney Disease

In this study, CKD was defined based on the NKF-KD0QI guidelines. The guidelines rank the status of the kidney damage based on the creatinine clearance. As such, the eGFR cut-off levels were used to determine the five stages of CKD.

Anaemia

It is defined using levels of haemoglobin. The levels vary between men and women based on the health status of the patient. For men, concentration below 13.0 g/dl was used to define anaemia. For women, the level was less than 2.0 g/dl.

Erythropoietin

Erythropoietin is an essential hormone produced in the liver and the kidney to enhance the production of red blood cells. The study concentrated on Erythropoietin levels. For the purposes of the study, the normal response to Erythropoietin for patients with CKD formed the basis of discussion.

Chapter 2: Systematic Literature Review

Introduction

There are different studies that have been conducted to investigate the implications of CKD and the related co-morbidities. The studies have been in the form of case studies, cross-sectional studies, and longitudinal studies. In relation to BMI and haemoglobin, the studies have mainly studied the relationships between obesity and CKD. In relation to haemoglobin, the focus has been the investigation of prevalence of anaemia in patients with CKD. The following section is an overview of CKD and review of the studies that have been conducted in the past. The focus is on the researches that touch on BMI and haemoglobin in patients with CKD.

Overview of Chronic Kidney Disease

Chronic kidney disease is classified as one of the major public health problems in many parts of the world. This has been due the increase the incidence and prevalence of the CKD in both the developing and developed nations. There are different stages of CKD, which are based on the glomerular filtration rate. The extent of the kidney damage is determined by albumunuria.¹⁷ In addition to being used as markers of CKD, the estimated glomerular filtrate rate (eGFR) and the albuminuria are classified as signifiers of cardiovascular disease.

In England, the prevalence of CKD as reported by use of eGFR and albuminuria in 2009/2010 was 6% for men and 7% for women. Kidney damage is the pathological abnormalities that can be traced by use of blood, urine and other imaging tests.¹⁸ A renal dysfunction is rated as chronic when the eGFR is 60ml/min/1.73m² for over three months.¹⁹ As stated, above, eGFR provides the basis for staging CKD. The following table is a guideline for the identification of stages of CKD. The stages are critical identifiers of the required therapeutic interventions for each stage.

Table 1: The five stages of CKD based on eGFR

For patients between stages 1-3, the severity is classified as mild to moderate. The eGFR is >30mL/min per 1.73m2. At this stage, patients are supposed to undergo screening interventions for the risk factors of CKD. The screening is followed by the analysis of the causes and treatment of the conditions such as the metabolic abnormalities such as obesity and other conditions such as anaemia. After reaching stage 3, the disease progresses to stage 4.

Here, it is termed as severe impairment. At this stage, the eGFR reduces to between 30-15 ml/min per 1.73m². At this juncture, the focus of the care providers is renal replacement. Finally, stage 5 has eGFR of less than 15 ml/min per 1.73m². It is normally established as renal failure. The major signs at the stage include uraemia. The condition is marked by raised levels of urea in blood and other nitrogenous wastes excreted by the kidney. The management of the CKD at this level includes dialysis or transplantation of the renal.

It is important to note that prevalence of any disease plays an important role in the assessment of the trends, establishment of the underlying determinants and in implementation of the procedures to manage and prevent CKD. In developed countries such as the UK, the concerned health professionals have put in place different policy initiatives to identify and manage CKD. They include the establishment of a reporting system for all eGFR data from the biochemistry laboratories.

This policy initiative makes it easy for the authorities to determine the prevalence and incidence levels and hence, help in the budgeting for the medical care services.²⁰ The policy measures taken by the UK health authorities present a great advancement in ensuring that quality of life is enhanced by ensuring that detected cases are treated before the CKD progresses to the final stages which are more expensive to treat.

However, it is worth noting that there is still need for a policy framework that puts into consideration the complications related to CKD which have a potential of lowering the treatment efficacy. Thus, a policy framework based on proper understanding of the co-morbidities will thus ensure a comprehensive awareness of the CKD.

Implications of Haemoglobin Levels among Patients with CKD

A study conducted by McClellan, Aronoff, and Bolton shows that the prevalence of anaemia is high among patients with renal dysfunctions.²¹ As such, anaemia is associated with increased chances of developing diabetes complications such as nephropathy and heart failure. In patients with diabetes, studies show that there are myriad of factors that contribute to the increased prevalence.

However, many studies have shown that majority of patients with renal impairment have functional Erythropoietin deficiency. It is also worth noting that the deficiency of Erythropoietin as a major cause of anaemia is not influenced by the severity of the renal dysfunction. This shows that despite the clear correlation of the anaemia and diabetes, there is the need for more studies to determine correction of the Erythropoietin. The situation results in the improved management of anaemia.

Kidney plays a great role hemopoiesis, oxygenation, and stimulation of haemopoeitic precursors found in the bone marrow. In many cases, the inability of the kidney to increase the release of Erythropoietin in order to counter the reduction in the haemoglobin level has been pointed out to be one of the causes for the development of renal anaemia. Therefore, there is evidence that functional Erythropoietin deficiency has a role in the diabetic nephropathy anaemia and thus the potential consequences for mortality and morbidity among the diabetic patients.

The definition of anaemia in relation to the haemoglobin level varies based on the gender age and the status of the individuals. For patients with CKD, the incidence of anaemia occurs when the haemoglobin levels are below 13.5 g/dl in males and 12.0g/dl in females (Appendix 2). The graph demonstrates the relationship between the haemoglobin and obesity. For example, many nations, the best practice guideline indicates that premenopausal women with haemoglobin level below 11.5 g/dl are anaemic, for adult males and post menopausal women it is 13.0 g/dl.

In relation to age, men aged above 70 years are said to be anaemic if the haemoglobin levels are less than 12.0 g/dl. Anaemia is manifested in all the five stages of CKD; however, its severity increases at the late stages of the kidney dysfunction. This necessitates the need for supplementation in order to correct the deficiencies. For instance, the prevalence of anaemia increases when the eGFR is 70ml/min or less for the adult males and less or equal to 50ml/min for the females. Many cross sectional studies have shown that anaemia is a major co-morbidity for CKD.

Deficiency of Erythropoietin

There are many factors responsible for the development of anaemia among patients with CKD. The main cause is the inability of the failing kidneys to synthesise EPO. In the body, the EPO is produced both in the liver and the kidney. The liver produces 10-15% of the EPO, while the rest is produced in the kidney. As such, the kidney is the main organ for providing the body with EPO.

The appropriate measure of the kidney function is the glomerular filtrate rate which varies depending on the sex, size of the body and age. For young adults, the GFR measures between 120 and 130 ml/min/ per 1.73 m². The levels decline with age to adulthood in which the kidney function losses more than half GFR by adulthood.²²

Anaemia presents adverse risk factors for patients with CKD. Among the patients with CKD, anaemia occurs at early stages more so for patients with diabetes compared to cases of CKD caused by other factors.²³ To re-emphasise, diabetes is one of the leading causes of kidney diseases. In addition, kidney is also a risk factor for diseases such as coronary heart disease. As such people who suffer from both anaemia and diabetes are likely to have faster progression of the CKD from stage 1-5 if proper care is not given.

A study was conducted by Lucile, Marie and Nicole et al (2012) to measure the levels of EPO among patients with CKD.²⁴ The patients constituted those with and without anaemia and the aim were to evaluate the concentration levels of haemoglobin in CKD patients. The study found that the response of EPO to the concentration of haemoglobin varied based on the average glomerular filtration. In most cases, the patients with anaemia but without CKD, had EPO was that was inversely correlated with haemoglobin concentration.

However, for patients with CKD, the correlation is deranged. In yet a similar study that examined the relationship between haemoglobin and the concentration of the serum EPO, a routine measurement of the parameters among 167 people without CKD and 333 CKD patients was conducted in a hospital in German.²⁵

The findings established that there exist a strong correlation between anaemia severity and the increase in EPO for the 167 people without CKD. For the population with CKD, the research established that as the CKD stages progresses, the correlation between EPO and haemoglobin gradually attenuated till it disappears at the final stages of CKD (stage 4 and 5).

Inhibition of Erythropoietin

Studies investigating the prevalence of anaemia in CKD patients show that it remains high despite the high levels of EPO. The implication is that CKD decreases the sensitivity of the bone marrow. It inhibits Erythropoiesis. According to another study, inhibition of the Erythropoiesis is common in uremic patients.²⁶ The cause is the uremic sera inhibitors, which is the mechanism for proliferation of hemosynthesis. As a result, it is common for health care providers to encounter progressive anaemia for patients who have not reached dialysis but have declining renal function. This is an attestation that the Erythropoietin tissues become less sensitive to the EPO for patients with CKD.

Body Mass Index and CKD

Studies have shown that the cause of death for people with the CKD is due to the combination of complications, such as cardiovascular diseases, diabetes, and anaemia. The cardiovascular complications are high among patients with high BMI.²⁷ The other contributing factors include severe anaemia, the presentation of the cases for treatment at later stages of the CKD, poor awareness of the kidney disease, and lack of clear policies to guide the diagnosis and treatment. High BMI signifies high cases of overweight and obesity which have grown exponentially across the globe.²⁸

These problems have reached pandemic levels. Studies have pointed out that obesity leads to increased mortality due to the consequent increase of cardiovascular diseases. Cumulative evidence suggests that there is an association between BMI and mortality. For instance, some studies have indicated that there is a low risk of death among patients with BMI of 20-27.5 kg/m2. This indicates that people with normal BMI have a survival advantage due to reduced risk of chronic disease such as diabetes and CVD.

In contrast to the findings from general populations, there are contradictory associations for BMI and mortality in patients suffering from CKD.²⁹ This is in relation to past studies that have shown that a low BMI was related to increased risk of death for patients with CKD. The main reasons for the findings have been attached to the baseline where low BMI is due to nutritional deficiencies that aggravate the CKD situation.

The contradiction is extended by other studies that have shown that there is no association between BMI and adverse manifestations of CKD. Due to the morbidity associated with CKD, it appears as if there is a difference between general population and those with CKD in relation to co-morbidities and mortality. In addition, there are differences in the way men and women exhibit pathogenesis and clinical manifestation of diseases. For example, a study about CKD, women were associated with a slower renal function decline and better survival compared to the males.³⁰

Even though the studies on the BMI in general population and patients with CKD are contradictory, they present the basis for further studies in order to understand the effects of BMI among the CKD patients. With regards to the relationship between obesity and anemia of inflammation, there have been several studies, some of which were inconclusive due to, perhaps their study design, for instance, the study on Mexican women showed that anemia is related to obesity and not nutritional iron deficiency.

The findings denote the crucial role of BMI plays in influencing the morbidity and mortality of renal diseases. The cross sectional study established that in dialysis patients, there is survival advantage for the patients with high BMI. The survival advantage can be attributed to the nutritional status of the patient.

The studies provide critical findings that can be useful when designing a comprehensive treatment therapy for the patients with CKD; however, they fail to look into the role of high BMI in obesity, CVD and other chronic diseases that may aggravate the condition of patients with CKD. The study contradict other cross-sectional studies that have pointed out that there are positive relationships between CKD and BMI, nevertheless there are longitudinal studies that have shown that higher BMI is a predictor of likelihood of renal dysfunction.

Relationship between Haemoglobin Concentration and BMI among CKD Patients

To inform the current research, the author carried out a review of other studies related to BMI, haemoglobin concentration, and CKD.³¹ For instance, there are extensive cross-sectional studies conducted to compare the relationship between obesity and CKD. A cross-sectional study in Norway by Hallan et al. evaluated 37,793 patients with a mean age of 50.2 years.³² EGFR was measured in which the results showed an association between people with a BMI of over 30kg/m² and CKD. In the study, there were no significant differences in gender.

In another cross-sectional study carried out in Japan, Nomura et al which evaluated 1,978 people who had a mean age of 60.8 years, similarly, the eGFR was measured³³ and The results showed that obesity was common in patients with CKD compared to those who did not have both among men and women. Another cross study was carried out by Shankar et al in Malay.³⁴

The mean age for the study participants was 58.1 years in which 2,783 participants were incorporated in the study. eGFR was measured and in this study, the association between MBI and CKD was only found among the men cohort. A control study in Sweden which compared 926 patients aged between 18 and 74 years for the relationship between diabetes and chronic renal failure found that a high BMI of between 30 kg/m² and 35 kg/m² was associated with chronic renal failure.

The findings from the above cross sectional studies are supported by the past longitudinal studies that have shown an association between chronic renal failure and haemoglobin both in diabetic and non diabetic patients.³⁵ As noted earlier, the variations established in the associations between BMI and chronic renal failures are attributed to different factors.

For instance, the racial differences and the sample sizes used. However, in a study in which 20,000 study participants were analysed in a cross-sectional study, it was established that there was positive correlation between BMI and CKD for both men and women.³⁶ For the cases of women, increased risk of progression of CKD was noted for the patients who were severely obese regardless of the age factor.³⁷ The findings show that the design of the intervention and management of the renal complications can be effective if there are programmes to reduce weight, treat hypertension and diabetes.

Summary of Literature Review

There are many studies that have suggested that anaemia leads to adverse outcomes in people with different health conditions. However, the presence of CKD has a modifying effect on anaemia. For example, anaemia can be an independent risk factor for chronic conditions such as CVD, however, the combination of anaemia and CKD leads to increased risk for development of coronary disease and stroke. The above literature review shows that both BMI and haemoglobin levels have a correlation with the progression of CKD.

From the review, it can be established that these factors play an important role in determining the progression of CKD. Even though there are no conclusive finding about the association between the BMI and CKD, the longitudinal studies have shown that high baseline BMI is a good predictor of future occurrence of renal dysfunction. On the other hand, cross-sectional studies concerning relationships between BMI and CKD have been contradictory. The contradictions have been attributed to variations based on gender and racial factors.

However, most of the studies have shown that high BMI is a precursor for faster progression of CKD. The rationale for the findings both in longitudinal and cross sectional studies mainly centre on the correlation of BMI and diabetes. Diabetes is one of the main factors that lead to various kidney problems. In addition, high BMI is associated with CVD and other chronic heart complications. The co-morbidities increase the severity of CKD. In relation to haemoglobin, the literature review has signified the role of Erythropoietin in CKD progression.

Suffice to say, the studies have provided a good basis for further investigation and understanding CKD. The knowledge from the studies can be primarily used in medical interventions for people with CKD. It is worth noting, however, that most of the studies were inconclusive in nature. In addition, the findings seem to be general and affected by variations such as gender and race. As such, there is the need for specific case studies that can be applied by policy makers in order to formulate policy-specific to some populations. Thus, the literature review lays ground for the current study that focuses on the relationship between haemoglobin and BMI for ICLD population with CKD.

Chapter 3: Research Methodology

Methodology

The phenomenon under investigation was the association between BMI and haemoglobin in a specified population with CKD. It was, therefore, essential for the researcher to devise a systematic way to understand the issue investigated. The procedure includes gathering information about the complications and how they affect the health status of the people with CKD.

The study aims at gaining scientific understanding on the correlations that exist between the CKD and the two co-morbidities associated with BMI and haemoglobin through the use of quantitative research methodology. The quantitative strategy uses measurable data to uncover patterns in a study. The data was obtained from the Imperial College, London spanning a period of 10 years. The data was extracted from the renal Diamond database.

Exclusion and Inclusion Criteria

Exclusion criteria

The initial data revealed a trend of a decrease of haemoglobin with increased BMI. However, the relation between decreased haemoglobin and BMI was not clearly noted with CKD IV and V reason being that with more advanced CKD there are other factors such as secondary or tertiary hyperthyroidism, mala-absorption of iron, or uraemia that have some effects on the bone marrow in addition, some the patients are on Erythropoietin stimulating agents.

Therefore, the study has excluded CKD IV and V from the analysis. The study has also excluded the population with low BMI with less than a count of 20 because the low BMI may have been influenced by nutritional deficiency.

Inclusion criteria

The criteria required that the study participants be patients with or without diabetes, male and female aged between 18 and 75 years who have a documented glomerular filtration, BMI, and haemoglobin measurements.

Study Design: Cross-Sectional Research

The commonly applied research designs in health setting include longitudinal and cross-sectional studies. It is important to note that other study designs can still be applied. However, for the current research, the study design is a cross-sectional study. In the health care setting, cross-sectional study it is viewed more as transversal study where the researchers observe certain trends in a population in a specific point in time. As a result, the data obtained provides a ‘snapshot’ of the situation as presented by the population under review.

In the current study, the researcher determined the stage of CKD by measuring the haemoglobin levels, the BMI and other parameters that pertain to the study. The subjects being studied may include the people with and those without CKD. The main advantage of using the cross-sectional study is because it provides the basis for comparing different populations at a specific point in time, i.e. providing a snapshot. For example, from the literature review, it was established that association between BMI or haemoglobin and CKD are sometimes influenced by factors such as age, nutrition and gender. Therefore, a cross-sectional study provides a way of looking at the different factors. Also, the design is descriptive at the same time and hence, the rationale for being applied in the current study.

Ethical Issues

The study did not require consideration of ethical issues. The reason is that all the data was obtained from the Diamond database.

The Sampling Procedure

The researcher realized that it was impossible to study the entire target population. As such, there was a need to acquire a section of population that is representative of the whole. The move forms the basis of sampling rationale. According to Denk, sampling is the process of selecting a subset of the target population.³⁸

It denotes having specific area that is being investigated and tentative knowledge on where the required information can be obtained from. As a result, in a systematic study, there are different sampling designs that are used. For the current study, cross-sectional study design, in which data was extracted from ICDLC, was applied.

The relevant data from the institution was obtained through non-probability sampling procedures. The aim of the current study was to establish the relationship between haemoglobin and BMI in patients suffering from CKD. It necessitated a large sample to ensure that the differences pointed out in the past studies are addressed. As such, the researcher settled for an institution that specialises in care delivery to people with diabetes and related complications, such as renal failure.

Rationale for Inclusion and Exclusion Criteria

The sample data was extracted from the ICDLC data base. The data covers all the patients who have attended the clinic for diabetic care since its inception; thus, the cross sectional data for a 10 year period. Even though the technique allows all the potential subjects to have an equal chance of being included in the final sample, there is the need to set parameters in order to ensure that subjects included are in line with the study objective the inclusion criteria entail all adult patients aged above 18 years, i.e. both males and females.

In addition, the study participant should be type 2 diabetes patients (diabetes mellitus), they should have a BMI of 20kg/m² or above, and the CKD should be between stages 1 to 3. The exclusion criteria are patients in stages 4 and 5 of CKD, those who are already on dialysis or patients who require dialysis. The CKD 4 and 5 were excluded because they are on exogenous EPO and IV iron therefore, to include them would mean to stop treating their anemia which is unethical. The patients on iron infusion, Erythropoietin supplementation and replacement therapy were as well be excluded, as those with BMI below 20 kg/m². The rationale for exclusion of the patients with low BMI was that they are likely to have nutritional deficiencies.

Sample Size

For the purposes of the current study, the researcher used a total of 64000 patients. The participants were drawn from ICLDC, a centre that provides specialised care for people living with diabetes. The sample was drawn from patients who had sought care in the centre and their diabetes and CKD related data was captured. There was, as a result, a large sampling frame. It is the reason why the researcher settled for the cohort of 64,000 patients. Out of these participants, only the non-insulin-dependent were included in the cohort population.

Methods of Data Collection

The application of the right data collection instruments is important. There are several data collection methods just as there are different sampling methods. The method of data collection is normally influenced by the research strategies, the point of collection, and the person to carry out the research. The use of the proper technique ensures that data is collected in scientific manner, minimises bias, and ensures consistency.

As a result, proper techniques of data collection enhance the accuracy, reliability, and validity of the study findings. In the current cross-sectional study, the data collection method entailed the review of the recorded data on patients with CKD in the ICLDC. The data captured a specific point in time for all the patients. The information collected included the last reading for each patient who visited the centre. The use of the last reading for each of the patients served as a major limitation to the data collection. The reason is that past measures of the study parameters were not captured in the data.

Criteria for Data Analysis

After the collection of the data, it was important to synthesise it in order to capture the useful information. This is obtained through data analysis. Data analysis is defined by Dixon as the process of cleaning, transforming and modelling data in order to establish the useful information that can be used to draw inferences.³⁹ There are different tools for analysing data.

The tools of data analysis entail software applications used to synthesise the extracted data and present it in a manner that allow easy drawing of correlations. Examples of software for the data analysis includes the use of excel functions or advanced tools such as SPSS. The present study relied on the statistical analysis using STATA 14.0., Multivariate analysis, and statistical test to determine correlation. For example, the correlation between the decreasing haemoglobin and increasing BMI, in which statistical significance was tested.

Overview of ICLDC

The Imperial College London Diabetes Centre (ICLDC) is a facility that offers outpatient services to people who are in need diabetes treatment. The state of the art centre is involved in training, research and creation of public health awareness. ICLDC has several centres, one in United Arab Emirate, the other in Abu Dhabi and the last one in Al Ain.

The centre was established in 2006 and since its inception; it has continued to offer important diabetes care services to patients. It boasts of having received over 800,000 patients since 2006. The centre operates in partnership with the Imperial College London in the UK. In general, the main mandate of ICLDC is to provide specialised care for patients with diabetes and related complications through diagnosis and management of the related conditions including kidney disease.

Chapter 4: Results And Analysis

Introduction

From the literature review it was established that the studies on the relationship between haemoglobin levels and anaemia have not been conclusive. Some of the past studies sought to investigate the relationship between anaemia and CKD or BMI and CKD. However, the aim of this study was to investigate how variation in haemoglobin affects BMI in patients with CKD.

The reduction in haemoglobin levels is used to determine the anaemic state of a patient. The study found that an increase on the BMI has different implications on the health of individuals both with and without CKD. The results and analysis section presents an analysis of the extracted data regarding the changes in haemoglobin levels and how such changes relate to obesity. Obesity is presented by increase in BMI above the normal.

Results

Overview

Data was obtained from 64,000 patients from the Imperial College Diabetes Centre who attended the clinics and their haemoglobin, BMI, blood pressure systolic, blood pressure diastolic, eGFR and other health parameters were tested. As outlined in the study objective, the main concern for this study was the relationship between haemoglobin levels and the BMI and the influences of gender and age. Even though 64,000 patients were involved in the study, the BMI and haemoglobin was not captured for all the patients. Table 2 is a summary of relationship between BMI and haemoglobin levels for the patients with CKD.

Table 2: Variation in haemoglobin levels with respect to BMI category and CKD groups

Table 2 above shows detailed result of relationship between BMI and haemoglobin. The total numbers of the patients were 51,730, in which four clusters of BMI were obtained based on the ascending order. In each cluster the mean haemoglobin was computed. The first cluster included the patients with BMI of between 20 and 30; the patients in the cluster were 28,063 while the mean haemoglobin was 132.61.

The second cluster ranged from 30 to 40 in which 20,094 patients were involved, with mean haemoglobin of 130.78. It is worth noting that in these BMI clusters, the age and gender factors were not analysed. The relationship established in table 2 is presented in figure 1. From the analysis, it can be demonstrated that as the haemoglobin level decreased the BMI were seen as increasing.

This table shows the mean and standard deviation of haemoglobin with the approximate number of patients within each BMI grouping.

Mean and Standard Deviation

BMI; body-mass index: kg/m2

The table above excludes BMI of less than 20. The reason is that such individuals are likely to have nutritional deficiencies. The total number of patients is over 50,000. The majority have a BMI of between 20 and 30 (n=28063) and 30 to 40 (n= 20094).

Association between BMI and Haemoglobin

The table above demonstrates the direct Association between body-mass index and haemoglobin. There are 54,027 observations. The p value of the model is highly significant.

The r² shows the amount of variance of haemoglobin explained by body-mass index. In this case, the body-mass index explains a 0.15% of the variance in haemoglobin. The two-tailed p value tests the hypothesis that each coefficient is different from zero. In this case, the body-mass indexes are statistically significant in explaining the relationship between BMI and haemoglobin. The coefficient shows that for each one point increase in body-mass index, the haemoglobin decreases by 0.105.

The figure above depicts how patients with high BMI are associated with decreased levels of haemoglobin.

Variation between haemoglobin and BMI based on CKD stages

In addition to the analysis between BMI and haemoglobin, further assessment was done to determine how the various stages of CKD related to the two parameters. The CKD stages analysed were 1, 2, and 3. The four clusters of BMI were maintained in order to ensure consistency of the results and enhance understanding of the variations. In this category, 40,640 patients were analysed.

The results showed that the mean haemoglobin decreased as the CKD progressed from one stage to the next. This was the case for the four BMI clusters as analysed and presented in figure 1. However, comparisons based on the BMI clusters did not show linear regression. For example, for BMI group between 20 and 30, the mean haemoglobin was 13136.42±16.95 for CKD stage 1, 131.73±15.91 for CKD stage 2 and 123.4±16.63 for CKD stage 3. For the BMI group 30-40, the mean haemoglobin for CKD 1, 2, and 3 was 132.73±17.24, 128.09±15.00 and 121.72±15.70 respectively.

Table 6 above is a Multiple Regression analysis of various factors contributing to a drop in levels of haemoglobin among patients. There is a statistically significant regression observed within the haemoglobin and glomerular filtration rate (ml/min/m2) BMI (kg/m2), glycosylated haemoglobin (HBA1c), and urinary microalbumin (MG).

Table 7: Variations in haemoglobin levels within BMI and CKD groups

Table 7 above illustrates the variations in levels of haemoglobin within BMI and CKD groups

Table 8 above shows the mean of haemoglobin levels.

The graph shows that an increase in BMI is associated with reduced levels of haemoglobin for each CKD stage. Figure 2 show that there is a significant drop in haemoglobin as the BMI increases. Furthermore, there is a decrease in the haemoglobin levels as the severity of CKD increases. For example, as the BMI for patients in CKD stage 1 increased, there was a noticeable drop in the haemoglobin levels. Table 9 below is an extraction of the changes.

Table 9: Changes in haemoglobin in haemoglobin and BMI for the three stages of CKD

The table represents the changes in haemoglobin in haemoglobin and BMI for the three stages of CKD. As pointed out, the measurements for haemoglobin levels were not obtained for all 64,000 CKD patients. As a result, the data was analysed for specific measurements based on the subjects who met the required parameters. For example, the PTH, ferritin and vitamin D2 level values are reasonable for clinical data obtained. However, only 3642 patients were recorded for ferritin.

Other measures with substantial readings included the eGFR with 45,201 patients, vitamin D measurements with a cohort of 50,739 patients, and micro-albumin measurements that had a cohort of 22,068 patients. Throughout the data analysis and subsequent discussion, the variations in the number of subjects were taken into considerations. Table 5 below is a summary of the analysed data. It is important to note that this is the synthesised data which has also taken into consideration the missing measurements for some parameters among the subjects.

Summary of Synthesised Data

Table 10 shows that an increase in BMI was related to a significant decrease in haemoglobin. In order to establish the correlation for the subjects that had the measurements for haemoglobin and BMI, a regression analysis was carried. Table 6 is a summary of the association between the BMI and levels of haemoglobin for 54027 patients.

Correlation between BMI and haemoglobin based on linear regression

As presented above, the linear regression helps in the determination of the correlation. For example, from the analysis, the p value of the association is highly significant while there is variance based on the haemoglobin levels as influenced by the changes in BMI. In addition to the linear regression, a multivariate analysis was undertaken to investigate the BMI and the glomerular filtration rate. The glomerular filtration rate was determined by the modified MDRD equation.

Regression analysis for relationship between BMI and glomerular filtration

Table 12: Regression analysis for relationship between BMI and glomerular filtration

*** p<0.01, ** p<0.05, * p<0.1

The table above is an indication that there is a relationship between the predictor variables as established by the association between the BMI and eGFR at 6.2%. The coefficient shows that with an increase in BMI there is a decrease on haemoglobin levels by 0.450 while an increase in GFR increased the haemoglobin level by 0.184.

The two-tailed P value test shows that there is a significant effect of glomerular filtrate and BMI on the level of haemoglobin. In addition to the haemoglobin, BMI, and glomerular filtration, a multivariate regression analysis was carried out to examine the relationships of vitamin D2, PTH and glycosylated haemoglobin. Table 13 is a summary of the multivariate regression.

4.3.3. Multivariate regression analysis of vitamin D2, PTH, and glycosylated haemoglobin

Table 13: multivariate regression analysis of vitamin D2, PTH and glycosylated haemoglobin

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

The multivariate regression analysis shows that R squared of 0.087 which is equivalent to an 8% of the variation of haemoglobin with the changes in BMI, GFR, vitamin D, PTH and systolic blood pressure and glycosylated haemoglobin. The two-tailed T value reveals that the vitamin D2 level is not significantly related to a haemoglobin reduction. However, the other parameters are statistically significant at (P< 0.05).

From the table it can be established that the significant single tailed T value reveal that the most important variables in haemoglobin are glomerular filtration and body-mass index at 48.29 and -33.44 respectively, the other parameters PTH, systolic blood pressure and HbA1c are -5.05, 12.98 and 10.85 respectively suggesting that they are weaker correlating factors. However, this is statistically significant. The glycosylated haemoglobin shows that an increase leads to a subsequent increase in the haemoglobin concentration.

An increase in the glycosylated haemoglobin results in an increase of the iron concentration. This is due to the fact that the function of glycosylated haemoglobin is dependent on the concentration of the serum haemoglobin hence the association is established. Also, the results point a possible relationship between albuminuria and vitamin D, i.e. an increase in albuminuria being related to a drop in levels of vitamin D for the 25,015 patients is observed.

Levels of serum EPO

It is noted that EPO is a critical factor that is produced by the kidney. Studies conducted by various researchers indicate that most patients had a reduced production of EPO as the renal damage progressed.⁴⁰ However, at a given haemoglobin concentration, the response of EPO was normal. For example, the results showed that at the initial stages of EPO production was 66.7%. The results indicated that a change in CKD from stage 1 to two and then three showed a positive correlation with the decreasing EPO. For the present study, the analysis for EPO was not carried out. However, based on the past clinical tests, it could be presumed that EPO levels for the patients with the first three stages of CKD would remain the same. However, based on the findings that increase in BMI was related to reduction in haemoglobin, there is high likelihood of EPO resistance due the renal damage. In order to avoid the presumptions, there is the need for future studies to carry out the EPO measurement.

Chapter 5: Analysis And Discussion

Introduction

The findings presented in chapter four shows the various factors related to CKD. In the cross-study, the relationship between BMI with respect to the BMI clusters was analysed. Low haemoglobin levels and increased BMI were found to be the factors that present the complications faced by majority of patients with CKD.⁴¹ The low haemoglobin is a pointer of increased prevalence of anaemia while an increasing BMI signifies severity of obesity. Evidence shows that obesity mediates complications of CKD, cardiovascular diseases, and obesity.

The early detection of the possible complication due to low haemoglobin levels can lead to lifestyle changes that could improve the chances of diabetes early interventions and the initiation of the management programmes that can improve the quality of life for the diabetic patients. This is also important in reducing the burden of care which is normally very expensive for patients who manifest the complications. Based on the correlations presented in the results section, the following is a detailed explanation of the implications in the management of CKD. Also, the findings are critical in the design and implementation of policy framework for the treatment of people with CKD.

Characteristics of the Study Subjects

The study participants included CKD patients between the age ranges of 18 to 75 years. The total number of patients included in the study was 64,000 which included both sexes. Even though the data was obtained from ICLDL, the patients hailed from different places and hence, represented different ethnic and racial groups.

The fact that over 64,000 subjects were studied proves that the study sample was considerably large; and, therefore had the ability to draw generalisations that can be used within general population. The presence of people with varying age and from different ethnic groups ensured that the study was comprehensive and inclusive. The diversity captured in the sample helped in reducing shortcomings related to inferences drawn from homogenous populations.

Haemoglobin Variability

The variability of the haemoglobin can be evaluated within a patient and sometimes between clients in a group. Within the clinical practice context, the variability importance is within the patient. There are several methods that are applied to quantify the degree of variability which may include the coefficient of variation which focuses on the ratio of conventional SD to the mean. However, the data studied showed a simple characteristic of the relationship between the haemoglobin and obesity.

The higher the BMI, the lower the level of haemoglobin registered for a particular patient in the cohort used. It therefore, means that high body mass has a direct influence of the levels of haemoglobin, a finding that is significant for the study because it is suggesting the obesity interferes with the growth of haemoglobin. It can be deduced from the results of the analysis that the variability of the haemoglobin can be associated with the mortality.

For instance, among the analysed results show that mortality risk is low among clients who maintain consistent haemoglobin levels between 11.0 to 12.5 g/dl. However, should the haemoglobin maintenance level oscillated towards 11.0, the longer that level was maintained it predicated a risk of mortality (table 3). It should be Bourne in mind that in the study, the patient characteristics did not account for much in the variation of the haemoglobin variability metric.

According to the analysis above, haemoglobin variability is closely associated with morbidity and mortality, it is, therefore, assumed that both high and low levels are also associated with elevated death risks. It is, therefore, evident that obesity or high body mass correlates positively with mortality arising from either high or low haemoglobin activities.

In the cohort of 58,058 that was used in the study, it can be observed that the maintenance of haemodialysis patients showed an inverse J-curve in the association between haemoglobin levels and possible adverse outcomes and conversely, the maintenance of haemoglobin levels in the 11.5 and 13.0 g/dl represented the lowest mortality risk.

Relationship between EPO, Haemoglobin, and CKD Stages

The extracted data shows that that there was a trend of decreasing haemoglobin as the stages of CKD progressed. Similarly, the EPO for the patients with CKD was found to reduce as the disease progressed from stage 1 to 3. As pointed out in the results section, as the haemoglobin levels reduced as the disease moved from stage 1 to 3, the EPO also reduced. As a result, majority of the study subjects had low EPO which is predictive of possible mortality (Table 4). This can be attributed to the mechanism which is used for the production of the EPO.

For instance, as the renal failure increased, the kidney mechanism responsible for the production of EPO was negatively affected. As such, only a small percentage of less than 5% of the patients included in the study sample had the normal levels of EPO production based on given level of haemoglobin. The findings are an indication of the contribution of EPO in increasing the prevalence of the anaemia among the patients with CKD. From the results, it was evidenced that as the disease moved from stage 1 to 3, there was low level of EPO. These findings relate to earlier clinical studies that have explained these findings based on the general renal function.

A case example is a study conducted by McClellan, Aronoff and Bolton which showed that the prevalence of anaemia is high among patients with renal dysfunctions.⁴² As such, anaemia is associated with increased chances of developing diabetes complications such as nephropathy and heart failure. Similarly, in patients with diabetes, studies show that there are many factors that contribute to the increased prevalence of the anaemia. As the severity of the renal disease increases, the cells responsible for the production of EPO are partially or completely damaged.⁴³

The result is that the production of EPO is inhibited and hence, compares to the reduction in the haemoglobin levels. Earlier studies have pointed to the evidence that as the disease CKD condition progresses, the correlation between haemoglobin and EPO becomes deranged. In the present case, the correlation was not established due to the fact that the analysis concentrated on the initial stages of CKD, i.e. stage 1 to 3. The deranged relationship can be explained by reviewing the physiological processes that result in the production of EPO in the body.

The two organs that produce EPO are the liver and the kidney. Kidney is the main producer, responsible for over 85-90% of the EPO generated in the body. Therefore, as the kidney gets damaged, the EPO production reduces. In case of complete damage of the cells responsible for the production, the body is left to remain with less than 15% of the EPO synthesised in the liver. Thus, the deranged correlation that has been found in studies that have analysed the correlation in stages 4 and 5 of CKD.

It is also worth noting that the deficiency of Erythropoietin, as a major cause of anaemia, is not influenced by the severity of the renal dysfunction. The findings depicted in the present study are similar to those by Lucile which showed that the response of EPO to the concentration of haemoglobin varied based on the glomerular filtrate. The cytokine Erythropoietin (EPO) plays an essential role in the synthesis of the red blood cells in the human body.

The main function of EPO is to stimulate the production of the cells in order to compensate the destroyed red blood cells which results due to their short lifespan. It can also be explained by an evaluation of the role the kidney plays in the control of Haematopoiesis, oxygenation and in the simulation of haemopoietic precursors that are found in the bone marrow. In many cases the inability of the kidney to increase the release of Erythropoietin in order to counter the reduction in the haemoglobin level has been pointed out to be one of the causes for the development of renal anaemia.

The glomerular filtrate is the standard measure used to determine the stage of CKD in the present study. The cross-sectional study by Lucile, established that for patients with anaemia but have are free from CKD, the EPO was inversely correlated with the concentration of haemoglobin. On the other hand, for patients with CKD, the correlation became deranged as the disease progressed from stage 1 to the final stages due to the fact that majority of patients with CKD are likely to suffer from anaemia.

The findings are further supported by a research carried out in a German hospital which established that as the kidney damage progressed, relationship between EPO and haemoglobin attenuated till it disappeared in the final stages of the disease. Therefore, the correlation established in the current study is because the study focussed on the early stages of the disease, thus, if the analysis could have covered the final two stages of the CKD, there is likelihood that the findings would mirror the studies that have established the deranged correlation.

Similarly, James, Post, and Wilkes noted that the inhibition of erythropoiesis due to decreased sensitivity of the bone marrow makes the Erythropoietin tissues to be less sensitive to EPO for the patients in the advanced stages of CKD.⁴⁴ It can, therefore, be deduced that functional Erythropoietin deficiency has a role in the diabetic nephropathy anaemia and thus the potential consequences for mortality and morbidity among the diabetic patients.

Therefore, it is arguable that the relationship established in the study, as depicted in the scatter diagram, was only for the first three stages. As the condition moves to the severe state, this is likely to change. In order, to ascertain the correlation of EPO and haemoglobin levels at the advanced stages of CKD, there is need to analysis the data for the patients in the fourth and fifth stages. Similarly, there are studies which have pointed out that the main cause is the failure of the diseased kidneys to synthesise EPO.

For example, the EPO is produced both in the liver and the kidney; however, the liver produces 10-15% of the EPO while the rest is produced in the kidney.⁴⁵ This makes kidney to be the main organ that provides the body with EPO. The appropriate measure of the kidney function is the glomerular filtrate rate which varies depending on the sex, size of the body and age.

For young adults, the GFR measures between 120 and 130 ml/min/ per 1.73 m². The levels decline with age and the kidney function losses more than half GFR by adulthood.⁴⁶ It is important to note that prevalence of any disease plays an important role in the assessment of the trends, establishment of the underlying determinants and in implementation of the interventions to manage and prevent CKD.

Clinical investigations have shown that patients suffering from diabetes have a higher degree of anemia in relation to the extent of renal dysfunction compared to the patients with other causes of renal impairment. There are myriad of factors that have been given as responsible for the onset of anemia in patients with diabetes mellitus. Some of the factors include autonomic neuropathy which adversely affects production of Erythropoietin (EPO). The condition also damages renal interstitial and, therefore, causes systematic inflammation of the kidney.

The end result is the inhibition of the production of EPO. Studies that have examined hematologic and hematinic parameters among diabetes patients have established how diabetes contributes to increased cases of anaemia. For example, in a retrospective analysis of hematologic parameters of type 2 diabetes patients showed that there was sustained decrease in hemoglobin for the patients in which a negative correlation was demonstrated between the levels of EPO and hemoglobin. As a result, it was concluded that anemia is a complication of chronic disease and is more severe in patients with diabetic nephropathy compared to patients suffering from other kidney diseases. EPO deficiency is therefore, associated with nephropathy.

Role of Vitamin D in Patients with CKD

One of the key parameters captured in the extracted data were the varying levels of vitamin D among the patients. For instance, the results showed that there was remarkable reduction in the level of vitamin D in the blood for CKD patients. Vitamin D deficiency is defined by levels less than 12 mg/ml. In the current study, the data extract from ICDLC showed that majority of the CKD patients suffered from Vitamin D deficiency.

The depiction can be explained by earlier studies that established that patients with kidney disease are found to have reduced activity of the 1- α hydroxylase in the kidneys; this enzyme is responsible for the activation of 25-hydroxyvitamin D to the active form of 1, 25-dihydroxyvitamin D.⁴⁷ The active form plays a critical role in the pancreatic function and hence its importance in management of diabetic patients and other conditions that depend on the healthy functioning of the kidney. There are different mechanisms through which Vitamin D is made available to the body; they include eating foods that are rich in the vitamin, through the ultraviolet B radiation from the sun or by taking supplements.

As the CKD progresses, there is evidence of the reduction of the active forms of the vitamin, which are the 1, 25 dihydroxy vitamin D and calcium. In general clinical manifestations, the situation is followed by the increase in serum phosphate levels which result in secondary hyperthyroidism as signified by the elevation of parathyroid hormones (PTH). This condition is responsible for bone disease that is known as the renal osteodystrophy. As a result, the CKD patients suffer a low vitamin D level which negatively affects the outcome of the dialysis.

The low levels of vitamin D observed in the study are supported by past studies. For instance, the review of the literature indicated that CKD leads to complications such as hypertension, albuminuria, and diastolic dysfunction. Vitamin D has a role in remedying the complications; thus, a deficiency in vitamin D can impair the treatment.

Clinical trials and laboratory experiments have shown that vitamin D helps in reducing albuminuria in animal models treated for kidney diseases.⁴⁸ For humans, there are different stages of CKD, which are based on the glomerular filtration rates. Studies also show that the extent of the kidney damage is determined by albumunuria.⁴⁹ In addition to being used as markers of CKD, the estimated glomerular filtrate rate (eGFR) and the albuminuria are classified as signifiers of cardiovascular disease.

In this relation, the kidney damage has been viewed as the pathological abnormalities that can be traced by blood tests, urine and other imaging tests.⁵⁰ The definition forms the foundation for understanding the current findings. As such, the renal dysfunction is described as chronic when the eGFR is 60ml/min/1.73m² for over three months.⁵¹ As stated, above, eGFR provides the basis for staging CKD. Thus, based on the findings it is worth emphasising that vitamin D plays a critical role in enhancing the function of the kidney. Similarly, the kidney has a role in enhancing the absorption of the micro-nutrient.

This is supported by various studies which have demonstrated that vitamin D has a supporting role in the pancreatic function. Consequently, the supporting role gives it a special function in patients with diabetes type 2 which is caused by the intolerance of glucose.⁵² Vitamin D has an exclusive effect on how insulin responds to glucose stimulation; consequently, among the individuals without CKD, the function of vitamin D is depicted by variation in glycaemic control based on the seasons of the year. For example, the glycaemic control for patients with diabetes type 2 is worse during the winter, a phenomenon that is attributed to the prevalent of the hypovitaminosis D during the cold season.

Research has also established that diabetes is one of the major causes of kidney diseases. Consequently, the level of vitamin D indirectly affects the CKD status. Due to the cross-sectional nature of the study, the trend of vitamin D that exists among patients with CKD was not established. The snapshots data provided the levels of vitamin D for the patients in the last day of visit; thus, the data cannot be entirely relied on to form conclusive argument about depictions of vitamin D among the patients.

As such, there is need for future studies to investigate the 25-OHD concentration and its effects on the development or lack of CKD. Nevertheless, from the snapshot data obtained in the current study, it can be inferred that many patients had low levels of vitamin D, and it was viewed as a possible predictor of the relationship between the eGFR and vitamin D. Putting into consideration the fact that active vitamin D plays a role in improving the status of patients with chronic diseases, such as CVD and renal dysfunction; there is a need for health policies makers to ensure that therapies for people with CKD should include vitamin D supplements.⁵³

Haemoglobin and CKD

The present data analysis showed that the haemoglobin levels reduced as the BMI increased. Similarly, the levels decreased as the CKD progressed from stage 1 to 3. These variations are an attestation of the past studies that found that the severity of anaemia increases as the renal dysfunction becomes worse. The increase in severity increases the mortality of the patients if care is not given on time. The findings of this study are supported by several studies that have examined the status of haemoglobin in populations with and without CKD.

The graph (App. 3) offers a clear demonstration that haemoglobin levels fluctuate among the patients with CKD; they can be below or above the recommended concentration levels.⁵⁴ Based on the past studies that have been conducted to examine the levels of haemoglobin in patients with CKD, it has been shown that the fluctuation of haemoglobin relates with the degree of the renal dysfunction. In clinical settings, haemoglobin is used to determine the anaemic status of the CKD patients. The different factors that contribute to anaemia include the deficiency of vitamin B12, iron, foliate and the inability of the body to produce enough Erythropoietin.

The variation in haemoglobin levels is also affected by different factors. For instance, haemoglobin levels below 13.5 g/dl among men qualifies the person to be termed as anaemic, while for women, levels below 12g/dl are termed as anaemic. Studies have demonstrated that low haemoglobin levels are evidenced in all stages of CKD. However, the haemoglobin levels are seen to vary based on the race, age and gender. For instance, past clinical studies have observed that as people age, the haemoglobin levels decrease.

This is more evident among women compared to men. Similar studies that have examined the status of haemoglobin levels have also pointed out that black patients have low haemoglobin compared to whites.⁵⁵ Despite the differences, the studies investigating the phenomenon have not shown significant variations in the ESA response based on the age, race or gender. Thus, in the treatment of the patients with CKD, there is the need to individualise the treatment. This is important in order to take care of the individual needs of the patient. In addition, the inconclusive nature of most of the clinical investigation necessitates the individualised treatment.

As observed earlier, low haemoglobin levels are used to determine the anaemic status of people. For the patients with CKD, there are underlying similarities in the mechanisms for the development of anaemia. However, there is also evidence that show that there exist differential responses to anaemia between men and women. In the current analysis of the data from the ICDLC, the differences between the haemoglobin levels between the women and men was very small for the patients whose haemoglobin levels were captured and analysed.

The contributing factors of death for CKP patients include severe anaemia, presentation for the cases for treatment at late stages of the CKD, poor awareness of the kidney disease, and lack of clear policies to guide the diagnosis and treatment. High BMI is a reflection of high cases of overweight and obesity.⁵⁶ As pointed out, anaemia is more prevalent for patients with diabetes. Besides, both obesity and anaemia have been categorised as risk factors for mortality for diabetes patients In relation to prevalence, anemia is 2-3 times more prevalent in people with diabetes mellitus compared to those without the diabetes type 2.

The analysis of the data indicated that there is an inverse association between the CKD and haemoglobin. However, the studies concentrated on levels of CKD where the renal replacement therapy had not started. Due to the cross-sectional nature of the current study, the risk of mortality due to reduced levels of haemoglobin, as identified in longitudinal studies, was not established in the study.

The longitudinal studies have also analysed the association of haemoglobin levels and mortality based on gender, a factor which was not examined in the present study. For example, it has been suggested that the risk of mortality due to CKD decreased among women with an increase of haemoglobin levels of up to 13 g/dl.⁵⁷ The implication for the findings is that women who have started renal replacement therapy are more likely to experience the effects of anaemia due to the low haemoglobin levels recorded for people whose renal system has failed.

To re-emphasise the situation of the current study, these findings could not be ascertained as the analysis was limited to patients who have not reached the stage of renal replacement therapy. Furthermore, the cross-sectional observational study did not examine the mortality associated with CKD. It is worth noting that there are very few studies that have investigated the haemoglobin variance in women compared to men. There is need, therefore, for further researches that could specifically evaluate the gender-specific effects by application of longitudinal data instead of cross-sectionals data which only provided the situation at a given time.

CKD and Risk Factors Associated with Lifestyle

There are different risk factors associated with CKD. As shown in the results, an increase in BMI was related to the increased risk of CKD progression to the next stage, which points to obesity as one of the key risk factors for kidney disease complications. In addition to obesity, another risk factor that was captured in the data was effects of smoking. The results showed that exposure to smoking increased the risk of CKD.⁵⁸ The findings are in line with previous studies that have pointed out that there is evidence that smoking has adverse effects on the kidney just as obesity acts as a risk factor.

For example, a research conducted by Hallan et al.⁵⁹ showed that a BMI higher than 35kg/m2 was a significant risk factor for CKD.⁶⁰ This shows that many patients are exposed to combined risk factors of CKD such as obesity, smoking and physical inactivity. Bearing in mind that more men are likely to be involved in smoking than women, this may place men at higher risk of CKD. In addition, there is evidence that there are biological interactions between obesity and smoking because they are seen as influencing each other. There is, thus, the probability of gender differences due the variations in the risks related to lifestyle. This phenomenon was not analysed in the current study as the main focus was to examine the relationship between haemoglobin and BMI in patients with CKD.

Relationship between BMI and Progression of CKD

The analysis of the data extract showed that as the BMI increased, the severity of CKD also increased. These findings mirrors past studies that have explored the relationship between BMI and CKD. In other words, an increase in BMI is related to a reduction in the mean rate of glomerular filtrate. Due to the findings, it is important to explore the implication of increased BMI on CKD. As stated, CKD is a risk factor for cardiovascular diseases.

The relationship is mediated by an association that exists between diabetes and CKD, obesity, smoking and hypertension. As pointed out, obesity has become a great concern for health care providers due its increased prevalence and its role in preceding CVD and diabetes. As a result, high BMI denotes overweight and obesity and plays a role in mediating the association of other risk factors with CKD. Clinical studies have categorised BMI as continuous exposure for people with CKD. Hence, an increase in a unit of BMI is likely to increase the probability of CKD worsening.

In a longitudinal study, a follow up of the study subjects for 10 years showed that obesity increased the risk developing stage 3 CKD.⁶¹ In addition, overweight and obesity were found to contribute to the development of CKD stage three. An analysis of data from more than 300,000 people by HSU et al showed that there was a relative risk of renal dysfunction in obese and overweight people.⁶²

The relative risk was evidenced in class 1, 2 as well as extreme obesity. The relative risk increased as the obesity moved from one stage to the next. For example, in class 1 obesity, relative risk was 2.98; in class 2 obesity, relative risk rose to 4.68; while in extreme obesity, the relative reached 4.99; this was in comparison with people with normal BMI and with varying degrees of kidney dysfunction.

As shown in the study, an increase in BMI is related with a decrease in haemoglobin. This is an important finding that the health care provider and policy makers can capitalise on by putting in place policies to ensure that there is a coordinated monitoring of haemoglobin in relation to haemoglobin for patients presenting with renal complications.

In addition, the findings can form the basis for further investigation to explore the effect of EPO deficiency as well as establishing whether it precedes eGFR decline. It has also been pointed out that low haemoglobin is associated with anaemia morbidity which increases the cost of treating the patients with CKD. Therefore, there should be policies that advocate for preventive care such as interventions to reduce obesity and supplementation and prior treatment of infections that are likely to aggravate the haemoglobin levels.

Impacts of Anaemia Levels on CKD

Overview

Anaemia is one of the factors associated with decreased function of the kidney. The main symptoms of anaemia include depression, dyspnoea and fatigue. Anaemia also has other adverse consequences that lead to left ventricular hypertrophy and left ventricular systolic dysfunction.⁶³ These adverse effects accelerate progression of CKD to the final stages of the renal dysfunction and stroke; hence, the implication that patients with anaemia caused by CKD have high likelihood of being hospitalised.

Furthermore, the length of stay in hospital is prolonged for the patients, an implication of high cost of treatment. In general, anaemia reduces the quality of life ad increases mortality related to CKD. Anaemia is found in all stages of CKD which qualifies it as a major co-morbidity. It increases towards the final stages of the kidney failure while the prevalence of anaemia sets in if the creatinine clearance reduces to levels of below 70ml/min.

The findings of the current study did not show a great difference from other related studies that have examined the prevalence of anaemia among the CKD patients. This is true for both the developed and developing nations. A study carried out by Cnunwuba, Uchenna and Ngozi in Nigeria found out that there was progressive rise in the anaemia severity from 26.7% among the patients studied to 75.5% in stages 3 to 5 respectively.⁶⁴

The mean haemoglobin of the study subjects decreased with decline in the eGFR for the five stages of CKD. The results, thus, relate to the current findings that have indicated that the degree of anaemia is proportional to the extent of the renal damage. However, it is important to bear in mind that the current stage did not analyse the correlation past stage three of the disease.

The major mechanisms of anaemia related to CKD are the reduction in the response of EPO. For instance, the patients who have no CKD, the correlation between EPO and haemoglobin is negative. This negative correlation is reversed in the patients with CKD. For patients in the latter stages of CKD, the feedback regulation mechanism is blunted but may be maintained after haemorrhage and in patients in high attitudes. This is explained by the functions of bone marrow in case of blood transfusion in high attitude areas. The patients with CKD, the EPO levels are normally below the expected quantity for the degree of anaemia.⁶⁵

In the current study, EPO varied based on the mean GFR level. The results showed that levels of haemoglobin and EPO were negatively correlated. After testing the significance of correlation, r was -0.2 and p=0.04 for the study subjects that had an mGFR of above 30ml/min per 1.73m2. However, there was no negative correlation for the patients with the mGFR less than 30ml/min per 1.73m2. Further analysis showed that there lacked correlation for the patients that did not have or had anaemia.

In addition to anaemia, EPO was found to vary based on the age, BMI and iron status of the patients. For example, EPO was found to be higher in patients aged between 60 and 69 years, and had a BMI above the normal. In relation to gender, there was no relationship established. The findings confirm that there is a significant interaction between EPO, GFR and haemoglobin in the CKD stages 1 to 3. The findings also show that there are other factors that are responsible for stimulation of EPO other than GFR and haemoglobin.

Hepcidin and its effects

The systematic iron metabolism is regulated is regulated by Hepcidin. The enzyme is a small peptide hormone. It regulates homeostatic operations of systemic iron metabolism. It also mediates between the defence of the host and inflammation. The hormone is measured in human urine, plasma, and serum.⁶⁶ Thus, the Hepcidin controls the flux of iron into the plasma. The levels of Hepcidin in the body are influenced by the level of body iron.

For example, when the levels of iron are high, the Hepcidin increases in order to block the absorption of the iron from the diet. The expression of Hepcidin is low when the levels of iron are low. In addition, in case of anaemia or hypoxia, the Hepcidin is also found to be low. As a result, for people with iron deficiency, the Hepcidin is normally suppressed to very low levels.

Anemia resulting from the progression of CKD is non-inflammatory; because the pathogenesis of the anaemia in CKD is normally caused by the impaired production of EPO. However, in case of infection that results in inflammation, the inflammation may adversely affect the Erythropoiesis and lead to resistance of the Erythropoietin treatment. To advance the understanding of anaemia in patients with CKD, there are studies that have been conducted to measure the levels of Hepcidin among the patients.

The rationale was to find out its role in anaemia. The Hepcidin studies have been mainly been on the relation to the Ferritin levels.⁶⁷ For patients with CKD and not on hemodialysis, there is evidence of suppression of Hepcidin. For the CKD patients who are on Erythropoietin therapy, the levels of Hepcidin drop slightly, a depiction that there is negative correlation between Hepcidin and the Erythropoietin dose.

Chapter 6: Conclusion

Strengths and Limitations of the Study

The major strength of the study is the large population sample of study, a sample size of 64,000 patients with CKD. The study main focus was on the diabetic patients with chronic kidney disease. This ensured that the parameters observed provided the relationship that was being sought without being influenced by other factors.

In addition the data was obtained from a leading diabetes centre which has been receiving and keeping the patients data over time. As such, there were no cases of bias as only data recorded by professionals was used; hence, the use of complete data sets. Moreover, the data used covered patients from diverse origins, sex, and age, critical factors that ensured that inferences drawn from the study could be generalised.

Despite these unique strengths, the study had its limitations. One of the major limitations was the study design. The use of the cross-sectional study design meant that only a snapshot of data at a given time was analysed. This implied that trends that could be observed in case of longitudinal study were not captured.

Thus, it can be argued that static data was used which does not show clinical changes that the patients with CKD undergo. The reliance on data from one diabetes centre may also be limiting, an occurrence that could be associated with the selection bias and data capture failures. However, the fact that ICDLC is run by medical professionals helps to eliminate the selection bias.

Discussion and Analysis

The major focus of the study was the analysis of the association between haemoglobin and BMI in patients with CKD. The study has established important correlations that affect the health status of the patients with CKD. One of the key to the findings included the establishment that haemoglobin levels declined as the renal disease progressed from one stage to the next. The study also found that there was a relationship between the BMI and haemoglobin levels in which increase in BMI was associated with decline in haemoglobin (Appendix 1).

The findings formed the basis for determining the co-morbidities of CKD including anaemia, obesity, hypertension, and other renal dysfunctions. In general, the study established that there was an association between haemoglobin levels, BMI and CKD. The increased severity of CKD in obese patients was found to increase as the BMI increased. Besides, the BMI factor, the study did not conclusively establish whether there was a statistical significance for the relationship between the haemoglobin levels and sex. However, the normal fluctuations which are found in patients with CKD were noted among sexes but correlations could not be established.

Additionally, the study established that the main co-morbidities among CKD patients were anaemia and obesity and they mediate in the development of other chronic complications such as cardiovascular diseases and diabetes mellitus. It was also found that the level of haemoglobin varied among the CKD stages. Similarly, as the obesity increased, the level of haemoglobin was also found to decrease in the studied obesity clusters.

Endogenous EPO was also noted to be inadequate, a state attributed to the diminishing kidney function which is the major organ that has the function of producing EPO. Other crucial factors established in the study were the role of active vitamin D and calcium in enhancing the kidney function. The findings may point to the EPO insufficiency which is an early occurrence of the decline in CKD.

From the findings of the study, it is evident that there are many factors that can lead to complications for people with CKD. Some of the factors included individuals’ lifestyles and social behaviour including smoking, inactivity, and poor diet that increase the chances of being obese. The associations established are critical in promoting the understanding the CKD progression.

Therefore, comprehensive awareness and knowledge about the management measures for the debilitating conditions such as anaemia and obesity can enhance the quality care accorded to the patients. This is based on the fact that that obesity has been on the rise across the globe and, therefore, a significant risk for the development of the CKD.

Implications on Health Policy

To sum up, all the associations established in the study have clinical implications because they can be applied in the formulation of policies that ensure that there are comprehensive intervention programs for patients with CKD. Due to the variations established and possible differentiation based on age and gender, the policy should capture the need for individualised preventive and curative therapies that take into consideration the findings. It will enhance the quality of life for the patients with CKD and also reduce the cost burden associated with increased hospital stay due to the co-morbidities.

The findings of the study have a wide range of implications on policy formulation and implementation. Having established that the haemoglobin, obesity, and CKD have a relationship, the study findings will add to the body-knowledge of the effects of these factors and inform on policy and interventions programs in the management of the CKD.

The prevalence of the chronic condition can be alleviated by appropriate education and the development of interventions programs that would be focused on addressing the obesity as a way of preventing the escalation of the CKD. According to the study finding, the management and maintenance of the haemoglobin within the standard level can also be a way of managing the chronic disease outcomes.

Suffice to say, the three health conditions are interrelated and their combined management can have improved heal care and well being for the CKD. However, the most significant implication is that the policy makers can address themselves to the management of obesity and the maintenance of appropriate levels of haemoglobin as a preventive measure among populations at risk of CKD and other allied complications.

References

1. Caldararu CD, Tarta D, Pop R, Gliga M, Carasca E, Dogaru G. Body Mass Index and the Relationship with Chronic Kidney Disease in a Tertiary Care Hospital in Romania. Acta Medica Marisiensis. 2016; 62 (2): 225-9.
2. El-Achkar TM, Ohmit SE, Mccullough PA, D CROOK ER, Brown WW, Grimm R, Bakris GL, Keane WF, Flack JM. Higher prevalence of anemia with diabetes mellitus in moderate kidney insufficiency: The Kidney Early Evaluation Program. Kidney International. 2005; 67(4): 1483-8.
3. Arogundade FA, Barsoum.RS. CKD prevention in Sub-Saharan Africa: a call for governmental, nongovernmental and community support. Am J Kidney Dis, 2008; 51(1):515-23.
4. Cohen E, Fraser A, Goldberg E, Milo G, Garty M, Krause I. Association between the body mass index and chronic kidney disease in men and women. A population-based study from Israel. Nephrology Dialysis Transplantation. 2013 ; 28 (4): 130-5.
5. Ginawi IA, Ahmed HG, Al-hazimi AM. Assessment of risk factors for chronic kidney disease in Saudi Arabia. Hypertension. 2014;1 (2):1-4.
6. Gotloib L, Silverberg D, Fudin R et al. Iron deficiency is a common cause of anemia in Chronic Kidney Disease and can often is corrected with intravenous iron. Journal of Nephrology. 2006; 19 (1):161 -7.
7. Kalantar-Zadeh K, Aronoff GR. Hemoglobin variability in anemia of chronic kidney disease. Journal of the American Society of Nephrology. 2009; 20 (3):479-87.
8. Boudville NC, Djurdjev O, Macdougall IC, de Francisco AL, Deray G, Besarab A, Stevens PE, Walker RG, Ureña P, Iñigo P, Minutolo R. Hemoglobin variability in nondialysis chronic kidney disease: examining the association with mortality. Clinical Journal of the American Society of Nephrology. 2009; 4 (7):1176-82.
9. Mehdi U, Toto RD. Anemia, diabetes, and chronic kidney disease. Diabetes Care. 2009; 32 (7):1320-6.
10. Plantinga LC, Tuot DS, Powe NR. Awareness of chronic kidney disease among patients and providers. Advances in Chronic Kidney Disease. 2010; 17(3):225-36.
11. Sevitt L.H, Hoff brand A.V, Serum folate and Vitamin B12 levels in acute and chronic renal disease. Effect on peritoneal dialysis. British Medical Journal. 2009;2(1):18-21
12. James B. Post, B.M., Wilkes Michael F, Iron deficiency in patients with chronic kidney disease: potential role for intravenous iron therapy independent of Erythropoietin. International Urology and Nephrology. 2006, 38(1):719-23.
13. Foster MC, Hwang SJ, Larson MG, Lichtman JH, Parikh NI, Vasan RS, Levy D, Fox CS. Overweight, obesity, and the development of stage 3 CKD: the Framingham Heart Study. American Journal of Kidney Diseases. 2008; 52(1):39-48.
14. Garty M, Krause I. Association between the body mass index and chronic kidney disease in men and women. A population-based study from Israel. Nephrology Dialysis Transplantation. 2014; 28(2):11-15.
15. Descombes E,Hanck AB,Fellay G,Water soluble vitamins in chronic hemodialysis patients and need for supplementation. Kidney International Journal. 2013; 43:1319-1328.
16. Anaemia management in chronic kidney disease: National clinical guideline for management in adults and children. London: Royal College of Physicians [Internet] 2006 [cited 2016 July 4] Available: www.guideline.gov/content.aspx?id=9817.
17. Roderick PJ, Fraser S, Mindell JS, O’Donoghue D, Day J, Moon G. Change in prevalence of chronic kidney disease in England over time: comparison of nationally representative cross-sectional surveys from 2003 to 2010. BMJ open. 2014; 4(9):1-15.
18. Berhane AM, Weil EJ, Knowler WC et al. Albuminuria and estimated glomerular filtration rate as predictors of diabetic end-stage renal disease and death. Clinical Journal of The American Society of Nephrology: CJASN. 2011; 6: 2444-51
19. National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. American Journal of Kidney Disease. 2002; 39:1-266.
20. Aitken GR, Roderick PJ, Fraser S, Mindell JS, O’Donoghue D, Day J, Moon G. Change in prevalence of chronic kidney disease in England over time: comparison of nationally representative cross-sectional surveys from 2003 to 2010. BMJ open. 2014; 4(9):1-15.
21. McClellan W, Aronoff SL, Bolton WK. The prevalence of anemia in patients with chronic kidney disease. Current Medical Research and Opinion. 2004; 20 (1):1501–10.
22. Cohen E, Fraser A, Goldberg E, Milo G, Garty M, Krause I. Association between the body mass index and chronic kidney disease in men and women. A population-based study from Israel. Nephrology Dialysis Transplantation. 2013; 28(4)130-5.
23. Jonathan O. Cullis. Diagnosis and management of anaemia of chronic disease: current status. British Journal of Haematology. 2011; 154(3):289-300.
24. Lucile M, Marie M, Nicole C et al. Timing and determinants of Erythropoietin deficiency in Chronic Kidney Disease. Clinical Journal of American Society Nephrology. 2012;7(2):35-42.
25. Ferrh A, Teut R: Serum Erythropoietin concentrations in response to anemia in patients with Chronic Kidney Disease. Nephrology Dialysis Transplantation. 2007;22: 2900-2908.
26. McGonigle RJ, Shadduck RK, Fisher JW: Erythropoietin deficiency and inhibition of erythropoiesis in renal insufficiency. Kidney International. 2004;25:437- 444.
27. Kambham N, Markowitz GS, Valeri AM, Lin J, D’Agati VD. Obesity–related glomerulopathy: an emerging epidemic. Kidney International. 2011;59(4):1498–1509.
28. Valeri AM, Lin J, D’Agati VD. Obesity–related glomerulopathy: an emerging epidemic. Kidney International. 2007;9(1): 98–109.
29. Huang JC, Lin HY, Lim LM, Chen SC, Chang JM, Hwang SJ, Tsai JC, Hung CC, Chen HC. Body mass index, mortality, and gender difference in advanced chronic kidney disease. PloS one. 2015;10(5).
30. Chen SC, Chang JM, Hwang SJ, Tsai JC, Hung CC, Chen HC. Body mass index, and gender difference in advanced chronic kidney disease. PloS one. 2014;1(5).
31. Tanaka H, Shiohira Y, Uezu Y, Higa A, Iseki K. Metabolic syndrome and chronic kidney disease in Okinawa, Japan. Kidney International. 2006;69(2):369-74
32. Hallan S, de Mutsert R, Carlsen S, Dekker FW, Aasarød K, Holmen J. Obesity, smoking, and physical inactivity as risk factors for CKD: are men more vulnerable?. American Journal of Kidney Diseases. 2006;47(3):396-405.
33. Mura I, Kato J, Kitamura K. Association between body mass index and chronic kidney disease: a population-based, cross-sectional study of a Japanese Community. Journal of Vascular Health and Risk Management. 2009;5(1):315-320.
34. Shankar A, Leng C, Chia KS, et al. Association between body mass index and chronic kidney disease in men and women: population-based study of Malay adults in Singapore. Nephrology Dialysis Transplantation. 2008; 23(1):1910-1918.
35. Ohashi Y, Sakai K, Tanaka Y et al. Reappraisal of proteinuria and estimated GFR to predict progression to ESRD or death for hospitalized chronic kidney disease patients. Renal Failure. 2011;33(2): 31-9.
36. Cohen E, Fraser A, Goldberg E, Milo G, Garty M, Krause I. Association between the body mass index and chronic kidney disease in men and women. A population-based study from Israel. Nephrology Dialysis Transplantation. 2013;28(4):130-5.
37. Boulware LE, Troll MU, Jaar BG, Myers DI, Powe NR. Identification and referral of patients with progressive CKD: a national study. American Journal of Kidney Disease. 2006;48(2):192-204.
38. Denk T. Comparative multilevel analysis: proposal for a methodology. International Journal of Social Research Methodology. 2010;13(1):29-39.
39. Dixon-Woods M, Agarwal S, Jones D, Young B, Sutton A. Synthesizing qualitative and quantitative evidence: a review of possible methods. Journal of Health Services Research & Policy. 2005;10(1):45-53.
40. Lucile M, Marie M, Nicole C et al. Timing and determinants of Erythropoietin deficiency in Chronic Kidney Disease.Clinical Journal of the American Society of Nephrology. 2012;7(2):35-42
41. Mai E, Horio M, Iseki K, et al. Prevalence of chronic kidney disease (CKD) in the Japanese general population predicted by the MDRD equation modified by a Japanese coefficient. Clinical and Experimental Nephrology. 2007;11(2):156–163.
42. McClellan W, Aronoff SL, Bolton WK. The prevalence of anemia in patients with chronic kidney disease. Current Medical Research and Opinion. 2004;20:1501–10.
43. Malyszko J, Malyszko JS, Pawlak K,Mysliwiec M, Hepcidin, iron status, and renal Function in chronic renal failure, kidney transplantation, and hemodialysis. American Journal of Hematology. 2006; 81(2):832-7.
44. James B. Post, B.M., Wilkes Michael F, Iron deficiency in patients with chronic kidneydisease: potential role for intravenous iron therapy independent of Erythropoietin. International Urology and Nephrology 2006; 38(2):719-723.
45. Jonathan O. Cullis. Diagnosis and management of anaemia of chronic disease: current status. British Journal of Hematology, 2011; 154 (1):289-300.
46. Cohen E, Fraser A, Goldberg E, Milo G, Garty M, Krause I. Association between the body mass index and chronic kidney disease in men and women. A population-based study from Israel. Nephrology Dialysis Transplantation. 2013;28( 4)130-5.
47. Melamed ML, Thadhani RI. Vitamin D therapy in chronic kidney disease and end stage renal disease. Clinical Journal of the American Society of Nephrology. 2012 Feb 1;7(2):358-65.
48. Dhiman RK, Duseja A, Chawla Y. Asians need different criteria for defining overweight and obesity. Archives of Internal Medicine Journal. 2005;165(9):1069–1070.
49. Roderick PJ, Fraser S, Mindell JS, O’Donoghue D, Day J, Moon G. Change in prevalence of chronic kidney disease in England over time: comparison of nationally representative cross-sectional surveys from 2003 to 2010. BMJ open. 2014;4(9):1-15.
50. Berhane AM, Weil EJ, Knowler WC et al. Albuminuria and estimated glomerular filtration rate as predictors of diabetic end-stage renal disease and death. Clinical Journal of The American Society of Nephrology. 2011; 6(1): 2444-51
51. National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. American Journal of Kidney Disease. 2002; 39:1-266.
52. Pittas AG, Lau J, Hu FB, Dawson-Hughes B. The role of vitamin D and calcium in type 2 diabetes. A systematic review and meta-analysis. The Journal of Clinical Endocrinology & Metabolism. 2007;92(6):2017-29.
53. Pittas AG, Lau J, Hu FB, Dawson-Hughes B. The role of vitamin D and calcium in type 2 diabetes. A systematic review and meta-analysis. The Journal of Clinical Endocrinology & Metabolism. 2007;92(6):2017-29.
54. Gelber RP, Kurth T, Kausz AT et al. Association between body mass index and CKD in apparently healthy men. American Journal of Kidney Disease. 2005; 46: 871–880.
55. Kalantar-Zadeh K, Aronoff GR. Hemoglobin variability in anemia of chronic kidney disease. Journal of the American Society of Nephrology. 2009;20(3):479-87.
56. Kambham N, Markowitz GS, Valeri AM, Lin J, D’Agati VD. Obesity–related glomerulopathy: an emerging epidemic. Kidney International. 2001;59(4):1498–1509.
57. Sturm G, Lamina C, Zitt E, Lhotta K, Lins F, Freistätter O, Neyer U, Kronenberg F. Sex-specific association of time-varying haemoglobin values with mortality in incident dialysis patients. Nephrology Dialysis Transplantation. 2010;25(8):2715-22.
58. Carlsen S, Dekker FW, Aasarød K, Holmen J. Obesity, smoking, and physical inactivity as risk factors for CKD: are men more vulnerable? American Journal of Kidney Disease. 2006;47(3):396–405.
59. Hallan S, de Mutsert R, Carlsen S, Dekker FW, Aasarød K, Holmen J. Obesity, smoking, and physical inactivity as risk factors for CKD: are men more vulnerable?. American Journal of Kidney Diseases. 2006 Mar 31;47(3):396-405.
60. Hallan S, de Mutsert R, Carlsen S, Dekker FW, Aasarød K, Holmen J. Obesity, smoking, and physical inactivity as risk factors for CKD: are men more vulnerable?. American Journal of Kidney Diseases. 2006;47(3):396-405.
61. Yamagata K, Ishida K, Sairenchi T, et al. Risk factors for chronic kidney disease in a community–based population: a 10–year follow–up study. Kidney International. 2007;71 (2):159–166.
62. Hsu CY, McCulloch CE, Iribarren C et al. Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144(1): 21–28
63. Reza Afshar, Suzan Sanavi, Javad Salimi, Mahnaz Ahmadzaheh. H. Hematological profile of Chronic Kidney disease in Iran, in Predialysis stages and after initiation of Haemodialysis. Saudi Journal Kidney Disease Transplant. 2009; 20(2):368-371.
64. Chinwuba I, Uchenna I, Ngozi I. High prevalence of anemia in predialysis patients in Enugu, Nigeria. Nephrology Reviews. 2010; 2(1):14-9.
65. Shadduck RK, Fisher JW: Erythropoietin deficiency and inhibition of erythropoiesis in renal insufficiency. Kidney Intinational. 2004; 25(3):437-444.
66. Tussing-Humphreys L, Pustacioglu C, Nemeth E, Braunschweig C. Rethinking iron regulation and assessment in iron deficiency, anemia of chronic disease, and obesity: introducing Hepcidin. Journal of the Academy of Nutrition and Dietetics. 2012;112(3):391-400.
67. Mercadel L, Metzger M, Haymann JP, Thervet E, Boffa JJ, Flamant M, Vrtovsnik F, Houillier P, Froissart M, Stengel B. The relation of Hepcidin to iron disorders, inflammation and hemoglobin in chronic kidney disease. PloS one. 2014;9(6):e99781.

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