Introduction

The burden and magnitude of chronic kidney disease (CKD) is enormous especially in developing countries. CKD currently is one of the world’s major public health issues. Lifestyle related diseases are important causes of increased morbidity and mortality in the world today. The 2004 WHO report on global burden of disease includes lifestyle related diseases and kidney disorders in the top twenty leading causes of death [1].

The body of evidence for other modifiable risk factors such as lifestyle factors is growing as some studies suggest that tobacco use is positively associated with CKD [2,3] . Some other studies on the other hand have found no association between smoking and CKD [4,5 ]. Alcohol has been linked as cause of kidney disorders in some clinical and experimental studies [6,7]. Increased risk of CKD has been reported with obesity [4,8] but few studies have described an inverse relationship between BMI and CKD [9,10]. No studies have been done in developing countries.

In most developing countries, chronic glomerulonephritis often caused by infections and infestations may be the leading cause of CKD [11,12] followed by hypertension. Albeit, studies in some developing countries such as South Africa [13] and India ^{[14] suggest that lifestyle factors are emerging as important risk factors for CKD. Non communicable diseases including lifestyle related diseases are emerging as significant causes of morbidity and mortality in developing countries prompting the WHO to highlight the problem of double burden of diseases in developing countries [1].}

Presently in Nigeria, there is no known population based study on CKD, the last non-communicable disease nation-wide survey sponsored by the Federal Ministry of Health in 1997,[15] did not include screening for CKD. Hospital based studies suggest that end-stage renal disease (ESRD) constitutes about 8% of hospital admissions. [12]. Most importantly, in Nigeria as in many other developing countries, majority of the individuals afflicted with CKD are young and in their economically productive years usually in their 4^th decade of life.[12] Worse still, a large majority of them (>80%) first consult a Kidney specialist after they have reached the terminal stage[11]. These therefore underscore the need for screening for early detection of CKD.

In this arm of a larger project on screening for early detection and prevention of CKD in Nigeria, and bearing in mind the double burden of disease, the authors investigated several modifiable lifestyle risk factors (tobacco use, alcohol consumption, physical inactivity and increased BMI) associated with CKD in relation to markers of early CKD in a population-based study.

Method

Study area and study population

Study Population

Sample Design

Data Collection: Administration of Questionnaire, Clinical Evaluation and Sample Collection

Definitions

Significant alcohol consumption was defined as intake of 3 or more drinks. Heavy cigarette smoking was defined as smoking of 1 packet or 20 cigarettes/day for at least one year. Heavy snuffing was considered as use of about 35gram (equivalent to 1.2oz) of snuff per week daily for at least one year [18].

Obesity was defined according to the 1999 WHO criteria. Cutoff points for BMI were: overweight (BMI 25.0 – 29.99kg/m²) obesity (BMI ≥30 kg/m²) [19].

Abdominal obesity was based on IDF classification viz. waist circumference ≥ 94cm for males and ≥ 80cm for females were considered abnormal [20].

Hypertension was defined as systolic blood pressure ≥140 mmHg or

diastolic blood pressure ≥90 mmHg or and/or concomitant use of antihypertensive medications according to the WHO/ISH guidelines [21].

Estimated glomerular filtration rate (eGFR) was calculated using the Cockroft and Gault equation [22] which correlates well with measured creatinine clearance in Nigerians [23].

Creatinine clearance = (140-age) × weight (kg)

0.81 × serum creatinine (µmol/l)

For females multiply by a factor of 0.85.

Albuminuria was defined as the ratio of albumin to creatinine (ACR) in an untimed urine sample as recommended by The National Kidney Foundation Proteinuria, Albuminuria, Risk, Assessment, Detection, Elimination (NKF PARADE) and The American Diabetes Association in the assessment of proteinuria in CKD [24, 25]. The ACR was categorized as: a) normal, <30mg/g; b) microalbuminuria, 30 ~ 299 mg/g; c) macroalbuminuria, >300 mg/g. Macroalbuminuria equates to 1+ proteinuria. Proteinuria creatinine ratio (PCR) was used in this instead of ACR.

Markers of early CKD were taken as proteinuria (PCR ≥30mg/g), haematuria or estimated glomerular filtration rate (eGFR) stages 1 to 3 [26].

Statistical Methods

The Statistical Package for Social Sciences (SSPS Inc, Chicago, IL) version 16 statistical software was used for data analysis. Cross tabulation assessed the association between lifestyle risk factors and markers of chronic kidney disease as outcome variable. We examined the relationship between the various variables such as sex or gender, age, level of education or years in school, site (semi-urban or rural community), tobacco use, alcohol consumption, past history of hypertension, past history of DM, present history of hypertension and DM. The relationship between use of tobacco and CKD was examined by using heavy use of tobacco or less. We also examined the relationship between CKD and type of tobacco used (mostly as cigarette or snuff in the study area). We assessed alcohol consumption by number of drinks taken per day (≥3 or less).

Spearman’s correlation was used to assess these relationships. Significant variables were further analyzed using the stepwise method of multiple linear regression analysis to isolate possible predictors or determinants of CKD based on their level of importance. All tests were two-tailed with p<0.05 taken as statistically significant.

Ethics

The Institutional Review Board at University Nigeria Teaching Hospital approved the study proposal and questionnaires. Informed consent was obtained from each participant before administration of questionnaire and data collection. During the study, participants with untreated conditions identified during the examination were referred to their usual primary health care provider, secondary or tertiary care providers as was deemed necessary.

Results

Of the number screened, one thousand four hundred and fifty-eight (709 male and 749 female) respondents were analyzed and the others (73) did not have analyzable data. About two thirds of the respondents studied were from the semi-urban communities (540 male and 548 female respondents) and the other third were from the rural communities (169 male and 201 female respondents).

The study showed that the prevalence of markers of CKD in the populations studied was 26.8%. Prevalence of CKD increased with age, Table 1. The respondents with CKD had significantly higher mean age (52.3±12.4 years) than those without CKD (40.5±12.7years), p-value 0.001. When stage 3 CKD and presence of albuminuria were considered separately 18.6% of the participants had CKD stage 3 and 17.1% had albuminuria only.

The mean BMI was significantly lower in respondents with CKD (23.8±4.6kg/m²) than those without CKD (26.2±4.7 kg/m²), p-value 0.001. BMI was negatively and significantly associated with markers of CKD – correlation coefficient (r): -0.260, p < 0.001. Further analysis showed that odds ratios (ORs) (obese versus non-obese) [95% CI] for all respondents were 0.48 [0.33–0.68], p < 0.001; when the sexes were analyzed separately similar pattern was seen viz. female respondents – correlation coefficient (r): -0.266, p <0.001; ORs [95% CI] 0.48 [0.31-0.74], p-0.001 and male respondents correlation coefficient (r): -0.25822, p<0.001; ORs [95% CI] 0.43 [0.22 – 0.87], p <0.016. Similar trend was noted when overweight respondents (BMI >24.9 - <30kg/m²) was compared with those not overweight (BMI <25kg/m²): for all respondents, ORs [95% CI] 0.44 [0.33 – 0.58], p<0.001; female respondents ORs [95% CI] 0.45 [0.30 – 0.67], p<0. 001, and for male respondents ORs [95% CI] 0.43 [0.29 – 0.64], p<0.001.

The mean estimated glomerular filtration rate (eGFR) for the respondents with early markers of CKD was 61.6±23.8ml/min as against 92.1±22.2ml/min for the respondents without, p<0.001. Increasing age, past history of hypertension and presence of hypertension were associated with CKD, Table 1.

The association between those who took alcohol (≥3 drinks) compared with those who took less and CKD was significant, OR [95% CI] 2.67 [1.30 – 5.49], p=0.006, table 1. After controlling for variables such as age, sex, use of tobacco, presence of diabetes mellitus or hypertension there was no association between alcohol consumption and CKD, r=0.052, p-0.100. There was no significant association between use of tobacco when combined (i.e cigarette smoking and use of snuff) and presence of markers of chronic kidney disease (ORs [95% CI]: 1.30[0.87–1.93], p <0.196. However, further analysis showed that use of tobacco as snuff when considered alone was significantly associated with CKD no such association was found with smoking of cigarette, table 2.

Table 3 shows the Spearman’s correlation values for CKD and factors that affect it in the study population. Of all factors, decreasing BMI correlated best with CKD (r= - 0.260, p-value <0.001). BMI therefore had inverse relationship with CKD. Significant variables were further analyzed using the stepwise method of multiple linear regression analysis to isolate variables based on their level of importance. Decreasing body mass index, reduced physical activity, use of tobacco as snuff, waist circumference and alcohol were isolated as predictors with decreasing BMI being the best predictor, table 4.

Figure 1

Characteristics of the respondents by presence or absence of CKD

Figure 2

Prevalence of CKD with type of tobacco used

Figure 3

: Correlation table of the lifestyle risk factors with CKD

Figure 4

: Stepwise multiple linear regression analysis of lifestyle factors that correlate with CKD in respondents

Discussion

In this population-based study of adult Nigerians aged 25 to 64 years we found a high prevalence of early markers of CKD – 26.8%. In studies in developed countries, prevalence range from 7.2% in Iceland [27],10.2% in Norway [28] to 13.1% in US [29]. Whilst the US [29] and Norwegian [28] studies looked at people with CKD stages 1 to 4 which is close to stages 1 to 3 done in this current study, the study in Iceland essentially looked at participants who had stages 3 to 5 CKD. Other developing countries have documented prevalence rates of 12.4% [30], 13% [31] and 13.3% [32] in Congo, China and India respectively. These later studies however looked at respondents with eGFR <60ml/min (stages 3 to 5 CKD). The difference in the degree of CKD as represented by stages of CKD can mostly explain the discrepancy between our studies and others in the developing world.

This current paper however considers the contribution of lifestyle factors in prevalence of CKD in the study population. The use of tobacco was not associated with markers of early CKD. Interestingly, further analysis showed that the form of tobacco product used was relevant as respondents who used tobacco in form of snuff had significantly higher prevalence of CKD. This raises the possibility that the additives to the tobacco in snuff could be accountable for the risk of CKD in these respondents. While some population-based studies have demonstrated significant association between smoking and CKD even independent of confounders such as body mass index, physical inactivity, use of NSAIDs, alcohol consumption, hypertension, diabetes mellitus and others [2,3], other studies have found no association between CKD and smoking[4].

Alcohol has been reported as a possible risk factor for CKD in clinical and experimental studies and several pathogenic mechanisms have been suggested. Shankar et al [2] have shown in their study that heavy drinking is associated with CKD. In this current study, alcohol consumption increased the risk of CKD in respondents. But the effect was not independent. Also few participants consumed alcohol in significant quantity.

Living in the rural area seemed to be a risk factor for CKD. The reasons for this finding were not explored in this present paper as it is a subject for another study. We found a contradictory protective effect with increased BMI in this population i.e. the non-obese respondents had two fold odds of developing CKD than the obese. Most literatures suggest obesity [4,8] and metabolic syndrome as risk factors for CKD [33]. However, some studies done in Japan have found decreased body mass index as an independent risk factor for CKD [9,10]. This seems to have been borne out in this current study. We opine the use of Cockroft and Gault equation as possible explanation as extremes of weight are known to adversely affect the accuracy of correlation of eGFR with renal function using this formula. This indeed calls for research in this area to further elucidate the reasons for this observation. It is important to note that waist circumference a measure of abdominal obesity had positive correlation with CKD in this current study.

Of the variables tested, decreasing BMI, physical inactivity, use of tobacco as snuff, waist circumference and alcohol consumption predicted the occurrence of markers of early CKD. While alcohol consumption, use of tobacco as snuff and waist circumference had positive correlation, BMI and physical activity had inverse relationship with CKD.

In spite of the strengths of this study which include: the fact that this is a population-based study, there were some limitations for example: the cross sectional design of the study instead of longitudinal design which is better for establishing causality. The use of self report for alcohol consumption and use of tobacco may not be entirely accurate because the veracity of the response cannot be ascertained. Kidney function and indicators of kidney damage were based on single measurements. In assessing proteinuria, PCR was used instead of ACR which is preferred.

In conclusion, in this population-based study, the prevalence of CKD was high. The consumption of three or more servings of drink was found to be associated with chronic kidney disease. Use of tobacco as snuff was associated with CKD but not cigarette smoking. BMI had inverse relationship with CKD.

Sponsorship

This project was part sponsored by the International Society of Nephrology (ISN) through their Research Committee Programme for Detection and Management of Chronic Kidney Disease, Hypertension, Diabetes and Cardiovascular Disease in Developing Countries (KHDC) which offers grant for befitting proposals.

The results presented in this paper have not been published previously in whole or part, except in abstract format.

Acknowledgements

The authors acknowledge their gratitude to Dr Elvis N Shu, Pharmacology Department, College of Medicine, University of Nigeria for his invaluable guidance. We also appreciate Mr. Soludo Eze, the sociologist, Mr. Eric Obikeze, who assisted with translating the questionnaire and Mr. Eke U Kalu, the field worker who trained the interviewers.