According to K/DOQI clinical practice guidelines for Chronic Kidney Disease (CKD) evaluation, classification and stratification, the criteria for the definition of Chronic Kidney Disease is kidney damage for more than or equal to three months, as defined by structural or functional abnormalities of the kidney, with or without decreased Glomerular Filtration Rate (GFR), that can lead to decreased GFR, manifest by either pathologic abnormalities, or markers of kidney damage including the abnormalities in the composition of blood or urine, or abnormalities in imaging tests.¹OrGFR less than 60ml\min\1.73m2 for more than or equal to three months, with or without Kidney damage [1, 2].

The CKD, a silent killer has few symptoms and frequently goes unrecognized [3].

Though population based screening studies have been performed in developed countries, there are very few studies in developing world and especially in India where even though an attempt has been made to develop a national registry [4], one still does not know the true prevalence and incidence of CKD.

The burden of illness of CKD is high worldwide and outcomes and resources for care vary across countries irrespective of location. Hence earlier identification should improve outcome. The strategies to improve identification include increasing public awareness, professional education, changes in health care policy, delivery system, basic clinical and outcome research related to CKD [5].Many of the developing countries have no facility or programs to detect and evaluate CKD.Hence, it is of utmost urgency to start grass root programs to detect and educate the people and put in place both primary and secondary interventions of medical care. Early detection and education can help prevent the progression of kidney disease to kidney failure [6]. Late detection is the lost opportunity for making any life style changes and treating the aggravating factors [6].

The principal reported causes of CKD worldwide are diabetes mellitus, and hypertension associated with advancing age, obesity, and behavioral risk factors [7, 8]. CKD in Sub-Saharan African countries tend to affect adults with hypertension, diabetes mellitus, HIV, obesity, herbal medications, and chronic glomerulonephritis , all of them being the main contributing factor [9]. Recognized environmental risk factors for CKD include exposure to heavy metals (lead, cadmium, arsenic, mercury and uranium); agrochemicals; and nephrotoxic substances such as aristolochic acid, associated with Balkan endemic nephropathy, found in starfruit (Averrhoacarambola L.) and some Chinese herbal remedies [10]. Other CKD risk factors described are the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the infectious diseases leptospirosis, hantavirus, leprosy and malaria (endemic in Central America). Other rare causes include heat stroke in mine workers and repeated episodes of rhabdomyolysis.

There have been reports of increasing presence of CKD in rural and coastal areas especially as reported in Srilanka and Andhra Pradesh in India [11].

This Study area chosen was in the middle of a highly industrialized rural setting in the Southeast coast of India. As there were reports of heavy concentration of heavy metals (especially cadmium- more than 130 times the toxic limit) [12] in water tested in adjoining coastal areas and the presence of large numbers of patients presenting with CKD and the pressing need for addition of more dialysis spots, all this gave us the impetus to conduct this community based rural survey in coastal Pondicherry, India.

There is also a paucity of studies in rural industrialized settings. Hence this attempt to study the prevalence of CKD in such a setting.

To find out the prevalence and determinants of chronic kidney disease among adults in rural Pondicherry, India

Table 1 gives the background details of the study sample. The mean duration of residing in current living place was 43.29 years (+20.18 SD).

Out of 422 respondents 102 (24.2%; 95% CI- 20.2 - 28.5%) respondents had Chronic Kidney Disease (CKD) (Table 2). Among 102 CKD patients 9 (8.8%) had Stage 1 CKD, 75 (73.5%) had stage 2 CKD, 15 (14.7%) had stage 3a CKD, two (2.0%) had stage 3b CKD and one had stage 5 CKD. There were no significant sex differentials in occurrence and stages of CKD (Table 3).

In multivariate analysis three variables (age, nutritional status and chronic morbidities) emerged as significant predictors for the risk of developing CKD. There were rise in age, (60-69 years, PR: 2.36, CI: 1.36-4.07), (70-79 years, PR:2.83,CI: 1.53 – 5.25) and (≥ 80 years, PR: 4.17,CI: 1.76-9.88), poor nutritional status (underweight,PR: 2.26, CI: 1.05-4.89), (overweight, PR: 2.19, CI: 1.06-4.52), (obese,PR: 2.13 CI: 1.13-4.01) and at least one chronic morbidity (PR: 5.85, CI:1.38-24.78) were found to be independently associated with CKD (Table 4).

The number of respondents who tested positive for proteinuria was 119 out of the 422 people(28.19%).In the CKD group of 102 patients 89 respondents(with CKD) had only (minimal) +1 proteinuria(87.25%) as compared to 10 people out of 102 who had ++2 proteinuria and only 3 people had +++3 proteinuria. Respondents who had Diabetes mellitus were 122 out of 422 respondents (28.67%) and 131 out of 422(31.04%) respondents had hypertension. The people in the CKD group(102 patients) with diabetes mellitus were 31(30.39%) and those with hypertension in the CKD group(102 patients) were 24(23.52%).

43 people in the CKD group(42.15%) had no diabetes mellitus or hypertension but had (minimal)+1 proteinuria.

In the present study, we found that24.2% of the study sample had Chronic Kidney Disease (CKD) among 50 years and above in rural Pondicherry. Most of the CKD cases (73.5%) were at stage 2. In the present study, we found a higher prevalence of CKD especially in stage 3 CKD (17%).

The Nephrologist made a final diagnosis of CKD with GFR estimation and presence of proteinuria using K/DOQI Updated clinical guidelines - Stage 1 with normal or high GFR (GFR > 90 ml/min), Stage 2 mild CKD (GFR = 60-89 ml/min), Stage 3A moderate CKD (GFR = 45-59 ml/min), Stage 3B moderate CKD (GFR = 30-44 ml/min), Stage 4 Severe CKD (GFR = 15-29 ml/min), Stage 5 End stage CKD (GFR < 15 ml/min) [2].

The determinants for CKD were in advancing age with poor nutrition (underweight, overweight and obesity) and the presence of at least one chronic morbidity.

There have been only a few rural surveys for screening of CKD in Indian scenario. A large community-based screening in a geographical region closer to Chennai found a prevalence of 0.7% CKD [22] Another study in rural Karnataka, found the prevalence of CKD as 6.3% by GFR estimation using MDRD equation [23]. An PAN Indian Urban study by Singh et al. (SEEK Study) showed a prevalence of CKD as 17.2 percent [20]. Another Semi-Urban Indian study showed a prevalence of CKD in stage 3 to be 4.2percent [24, 25]. Yet another study by Agarwal et al. in Urban setting in Delhi, India found the prevalence of 0.79% for stage 3 and above CKD with a serum creatinine cut-off 1.8mg/dl (a very high cut-off value). However, they did not consider proteinuria and GFR in calculation [25, 26]. Studies from China [3], KEEP Study-USA [27], Singapore [28], Norway [29], Australia [30], Benin Togo-WestAfrica [31], KEOP study in USA [32],SHARE screening in HongKong [33], Japan [34] show a prevalence of CKD ranging between 4-15% of the adult Population and widely varying screening methods. Prevalence in North Central Province, Uva and North Western Provinces in the agricultural communities in Sri Lanka showed a CKD prevalence rate of 5-16.9% with more severe disease in the females [35].

Only three factors emerged as the predictors of CKD, which were advancing age, poor nutritional status and the presence of at least a chronic co-morbidity. Though advancing age and co-morbidities like hypertension and diabetes mellitus are well-known risk factors in causation and progression of CKD, the altered nutritional status (malnutrition and overweight /obesity) was a notable finding in this study. In the study from rural Karnataka the prevalence of diabetes was quite lower at 3.82% and the prevalence of hypertension was 33.57% [23]. Whereas other studies from rural India give similar prevalence of diabetes at 24% and that of hypertension at 32% [36].Yet another rural study from Pondicherry gives similar prevalence of Hypertension as 24% [37]. Gender, abdominal obesity, smoking, and co-morbities, were found to be significant factors in the rural study from Karnataka, India [23]. Obesity is known to cause a hemodynamic burden on kidneys that causes glomerular injury, elevated blood pressure and causes proteinuria [38]. Hence weight reduction in the early phase of life has to be advocated strongly to curb this epidemic. A high BMI is one of the strongest risk factors for new onset CKD [39]. Only a few studies have provided insights as to when malnutrition occurs during the course of kidney disease, similarly, whether early to moderate CKD is associated with some abnormalities in nutritional status or body composition is ill defined [40]. Malnutrition and inflammation complex (MICS) starts developing relatively early in the course of CKD and shows gradual worsening until ESRD is reached with mechanisms related to low GFR including decreased clearance of pro-inflammatory cytokines, volume overload, oxidative stress, carbonyl stress and decreased anti-oxidant levels [41].

CKD stage 3 and 5 are associated with a spontaneous reduction of the mean protein intake from1.0gm/kg bodyweight/day to about 0.5gm/kgm body weight per day accompanied by a reduction in energy intake [42-44]. There are little data on the prevalence of PEM in predialysis CKD stages, But a change in body composition including a reduction in body cell mass has been recently reported [45]. The prevalence of Protein Energy Wasting (PEW) progressively increases during the evolution of CKD. It is reported that 40% of the patients present with symptoms of PEW at the entrance in dialysis [46, 47]. There is strong evidence for a relationship which exists between malnutrition, inflammation and atherosclerosis [46-50].

The co-morbidities prevalent in CKD are also associated with inflammation and PEM. Also, acidosis may contribute to protein catabolism and reduction in lean body mass. But the fact is the causes and consequences of the PEM in CKD are not well understood [51].

A similar “rural clusters study” done recently in adults above 40 years (mean age 58years) in rural Bangaldesh, Pakistan and Sri Lanka have also reported older age, presence of diabetes mellitus and elevated blood pressure as factors independently with higher odds of CKD.Surprisingly the overall prevalence of CKD reported there was 38.1% with a high incidence in Sri Lanka (58.3%) [52]. Yet another recent prospective cohort study in adults between 40 and 75 years from Iran shows that older age, larger body mass, hypertension and diabetes mellitus are all associated with CKD.They also had a similar prevalence of 23.7% with CKD 3a and 3b prevalence of 20% and 3.3% respectively [53].

Hence, the traditional risk factors for CKD including older age, hypertension, and diabetes were all confirmed in our study.

The fact that majority of the CKD patients with proteinuria (87.25%) had only minimal proteinuria(trace to+1 proteinuria) and the fact that 42.15% of the respondents had no diabetes mellitus or hypertension but had trace to +1 proteinuria seems to point towards some other aetiology, other than conventional etiological factors like diabetes mellitus or hypertension. It is also known that CKDu(CKD of unknown aetiology often presents with only mild to moderate proteinuria [11, 35].

The findings of the present study are based on a representative sample from a rural setting of Pondicherry. Hence, the findings of the present study based on a sample can be generalized to the population in Pondicherry. We used the standard definition for the diagnosis of CKD by estimation of GFR by MDRD equation for each individual and patients with proteinuria were included as evidence of kidney damage. The analysis is robust and the confounders were adjusted to determine the factors responsible for the CKD. However, the limitations of the present study should be kept in mind. It is hard to make cause and effect relationship using the cross-sectional data as there is no information on temporality of events. Another limitation in this study was that a spot urine testing was done only once. Finally, the unavailability of isotope dilution mass spectrophotometry (IDMS) [12] negates a national uniform method to estimate serum creatinine in an Indian setting. Also, the repeated estimations of serum creatinine and proteinuria would have increased the Precision. Yet another limitation was that the occupational exposure of the respondents was not collected.

The public was involved in the initial discussions regarding the feasibility of this study, its importance and its implications for the lay public and patients in the future as such. Permission from the village elders, head men and their advisors was sought for initially.The questionnaire was shown to them and their opinion sought on the various headings in it. We also requested their help for the information dissemination, as we plan to screen in the next phase of the study, for looking in detail at the aetiology of CKD in this area.

Considering the higher prevalence of CKD in the study area, targeted screening of adult population should be undertaken as means of early detection, diagnosis, treatment and follow-up of at risk individuals to prevent further progression of CKD. A similar approach has been reported as medical outreach services to underserved populations in rural areas [54-56]. Another major implication is that if we would be to able to detect CKD earlier, in stage 2 and 3, a drastic lifestyle change may help in the prevention and progression of CKD. Acquiring evidence that current interventions to reduce CKD risk in the obese are efficacious and deployable, is an urgent priority to set goals and means for risk modification [57]. As CKD is also a major risk factor for cardiovascular morbidity and mortality, early detection of CKD is of paramount importance. Considering the possible role of environmental agents in industrialized communities, further investigation is required to confirm the link between the potential environmental pollutants with CKD [12, 58].

Strengths and limitations of this study

• As this was an exclusive rural based survey in an industrialized setting showing a higher prevalence of CKD, it is more representative of the population at large as a major part of the population resides here in the villages unlike an urban or a mixed group. Similar rural studies are rarely done / reported.

• The diagnosis of chronic kidney disease was based on a standardized estimation of the Glomerular filtration rate by the MDRD study equation and by the presence of proteinuria as a sign of kidney damage.

• The analysis is robust and the confounders were adjusted to determine the factors responsible for CKD.

• Estimation of serum creatinine and urine for proteinuria was checked only once. The repeated estimations of serum creatinine and proteinuria would have increased the precision of the study.

• Finally, the unavailability of isotope dilution mass spectrophotometry (IDMS)as a uniform method to estimate serum creatinine in an Indian setting is a limitation in the study.