Prevalence of chronic kidney disease and risk factors for its progression: A cross-sectional comparison of Indians living in Indian versus U.S. cities
Prevalence of chronic kidney disease and risk factors for its progression: A cross-sectional comparison of Indians living in Indian versus U.S. cities
Shuchi Anand 0 1
Dimple Kondal 0 1
Maria Montez-Rath 1
Yuanchao Zheng 1
Roopa Shivashankar 0 1
Kalpana Singh 0 1
Priti Gupta 0 1
Ruby Gupta 0 1
Vamadevan S. Ajay 0 1
Viswanathan Mohan 1
Rajendra Pradeepa 1
Nikhil Tandon 0 1
Mohammed K. Ali 0 1
K. M. Venkat Narayan 0 1
Glenn M. Chertow 1
Namratha Kandula 1
Dorairaj Prabhakaran 0 1
Alka M. Kanaya 1
0 Centre for Chronic Conditions and Injuries, Public Health Foundation of India , New Delhi , India , 2 Centre for Chronic Disease Control , New Delhi , India , 3 Division of Nephrology, Stanford University School of Medicine , Palo Alto, CA , United States of America, 4 Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialties Centre , Chennai , India , 5 Department of Endocrinology, All India Institute of Medical Sciences , New Delhi , India , 6 Rollins School of Public Health, Emory University , Atlanta, GA , United States of America, 7 Division of General Internal Medicine and Department of Preventive Medicine, Northwestern University , Chicago, IL , United States of America, 8 Division of General Internal Medicine, University of California San Francisco , San Francisco, CA , United States of America
1 Editor: Xu-jie Zhou, Peking University First Hospital , CHINA
Data Availability Statement: Since both CARRS
and MASALA are funded by NIH, data are publically
available. MASALA data access decided upon by
MASALA project committee; interested parties can
http://www.masalastudy.org/forresearchers/. CARRS data used in our analyses
have been submitted to the NHLBI; more
information available at http://www.nhlbi.nih.gov/
While data from the latter part of the twentieth century consistently showed that immigrants
to high-income countries faced higher cardio-metabolic risk than their counterparts in
lowand middle-income countries, urbanization and associated lifestyle changes may be
changing these patterns, even for conditions considered to be advanced manifestations of
cardiometabolic disease (e.g., chronic kidney disease [CKD]).
Methods and findings
Using cross-sectional data from the Center for cArdiometabolic Risk Reduction in South
Asia (CARRS, n = 5294) and Mediators of Atherosclerosis in South Asians Living in America
(MASALA, n = 748) studies, we investigated whether prevalence of CKD is similar among
Indians living in Indian and U.S. cities. We compared crude, age-, waist-to-height ratio-, and
diabetes- adjusted CKD prevalence difference. Among participants identified to have CKD,
we compared management of risk factors for its progression. Overall age-adjusted
prevalence of CKD was similar in MASALA (14.0% [95% CI 11.8±16.3]) compared with CARRS
(10.8% [95% CI 10.0±11.6]). Among men the prevalence difference was low (prevalence
difference 1.8 [95% CI -1.6,5.3]) and remained low after adjustment for age, waist-to-height
ratio, and diabetes status (-0.4 [-3.2,2.5]). Adjusted prevalence difference was higher
among women (prevalence difference 8.9 [4.8,12.9]), but driven entirely by a higher
prevalence of albuminuria among women in MASALA. Severity of CKDÐ-i.e., degree of
Funding: This work was supported by federal
funds from the National Heart, Lung, and Blood
Institute, at National Institutes of Health [Contract
#HHSN2682009900026C, CARRS study; #
R01HL093009, MASALA study]. Data collection at
University of California San Francisco was also
supported by the National Center for Research
Resources and the National Center for Advancing
Translational Sciences, at National Institutes of
Health [grant # UL1 RR024131]. Dr. Anand is
supported by National Institute for Diabetes and
Digestive and Kidney Health [grant # K23
DK101826]. Dr. Chertow is supported by National
Institute for Diabetes and Digestive and Kidney
Health [grant # K24 DK 085446]. The content is
solely the responsibility of the authors and does
not necessarily represent the official views of the
National Heart, Lung, And Blood Institute, National
Institute for Diabetes and Digestive and Kidney
Health, or the National Institutes of Health.
Competing interests: The authors have declared
that no competing interests exist.
albuminuria and proportion of participants with reduced glomerular filtration fraction-Ðwas
higher in CARRS for both men and women. Fewer participants with CKD in CARRS were
effectively treated. 4% of CARRS versus 51% of MASALA participants with CKD had A1c <
7%; and 7% of CARRS versus 59% of MASALA participants blood pressure < 140/90
mmHg. Our analysis applies only to urban populations. DemographicÐ-particularly
educational attainmentÐ-differences among participants in the two studies are a potential source
Prevalence of CKD among Indians living in Indian and U.S. cities is similar. Persons with
CKD living in Indian cities face higher likelihood of experiencing end-stage renal disease since they have more severe kidney disease and little evidence of risk factor management.
Historically, migration from low- and middle-income countries (LMIC) to high-income
countries (HIC) has conferred higher cardio-metabolic risk among the immigrant groups. For
example, three West African populations studied along ªthe migration ladderºÐliving in
Nigeria, Jamaica, and the U.S.Ðdemonstrated higher body mass indices in a stepwise fashion
]. Indian immigrants to London in the 1990s had higher body mass index, systolic blood
pressure, and fasting blood glucose compared with their siblings living in Punjab, India[
Japanese immigrants to Hawaii and California in the 1970s experienced a doubling in the
incidence of myocardial infarction compared with contemporaries living in Japan[
However, as many LMIC experience rapid urbanizationÐaccompanied by a rise in
consumption of energy-dense foods and declines in physical activityÐit is conceivable that the
burden of cardio-metabolic diseases in urban residents of LMIC now approaches that of
immigrants to HIC. In fact, recent data suggest that prevalence of diabetes mellitus is higher in
Indians living in Indian rather U.S. cities [
]. Whether this trend holds true for other
cardiometabolic diseases, particularly ones that are considered late manifestations, is not known.
We therefore compared data from the Center for cArdiometabolic Risk Reduction in South
Asia (CARRS) and Mediators of Atherosclerosis in South Asians Living in America (MASALA)
studies to: 1. compare the prevalence of chronic kidney disease (CKD) among Indians living in
Indian cities (CARRS) with Indians who have immigrated to U.S. cities (MASALA); 2. assess
whether differences in body size or diabetes prevalence explain any CKD prevalence difference;
and 3. among participants identified to have CKD in the two studies, describe the management
of parameters associated with progression to end-stage renal disease (ESRD).
The methodologies of the CARRS[
] and MASALA[
] studies have been previously described
in detail. Briefly, the CARRS Study is a community-based prospective study that employed a
multistage cluster sampling technique to capture the prevalence and incidence of
cardio-metabolic diseases in three major cities of South AsiaÐChennai and Delhi, India, and Karachi,
Pakistan. The study received approval for human subjects research from the Ethics
Committees of the Public Health Foundation of India and All India Institute of Medical Sciences
(Delhi), Madras Diabetes Research Foundation (Chennai), and Emory University (Atlanta).
We restricted this analysis to Delhi and Chennai (n = 12 271) as the laboratory in Karachi used
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different laboratory kits and equipment for serum and urine creatinine assays. To match
MASALA study entry criteria, we further restricted the analysis to participants aged 40 years
old without self-reported heart disease or stroke (n = 6537) (See Figure A in S1 File for study
flowchart). Of these, 5294 participants had complete data on albuminuria and serum
creatinine, and comprise the analytical group. Table A in S2 File demonstrates that while men were
more likely to have missing data, participants with and without data on markers of CKD were
similar in their age distribution and educational status.
The MASALA study is a prospective study investigating the prevalence and outcomes of
subclinical cardiovascular disease in 906 South Asian adults, aged 40 years and free of
physician-diagnosed cardiovascular disease. (Figure B in S1 File). This study invited random
samples of South Asians (identified as such from census tracts or surrounding counties using
surname identification techniques) living in the San Francisco Bay Area and greater Chicago
area to participate via mail. Study participants had been living in the U.S. for a mean of 27 ± 11
years. Institutional Review Boards at the University of California, San Francisco and
Northwestern University approved the study. In this analysis, we included persons who were born in
India (n = 757) and had complete data on albuminuria and serum creatinine (n = 748).
Correlates of CKD
Both the CARRS and MASALA studies obtained data on age, sex, household income, years of
schooling and highest level of education achieved, tobacco use, and use of medications using
standardized questionnaires. Both studies also obtained weight, height, waist circumference,
and hip circumference measurements using protocols similar to those employed for the U.S.
National Health and Nutrition Examination Survey (NHANES). For other demographic and
clinical risk factors for CKD and/or progression of CKD, we attempted to harmonize the
correlate definitions across the two studies (Table 1).
Accredited site laboratories processed participants' fasting blood and urine samples. Both studies
employed the same assay methodology for: fasting plasma glucose (hexokinase/kinetic method),
glycosylated hemoglobin (high performance liquid chromatography standardized to the National
Glycohemoglobin Standardization Program), lipid panel (enzymatic), and urine albumin
(immunoturbidimetric). To measure urine and serum creatinine, CARRS used the rate-blanked and
compensated kinetic Jaffe assay whereas MASALA used the enzymatic colorometric assay, both
traceable to isotope dilution mass spectrometry (IDMS) at the National Institute of Standards[
The two assays have been shown to have a nearly identical reference range [8±10].
Definitions of disease status
With the 2012 Kidney Disease Improving Global Outcomes (KDIGO) guidelines[
] as a
reference, we defined a participant as having CKD with albuminuria (albumin-to-creatinine
ratio 3.4 mg/mmol [30 mg/g]) and/or CKD-EPI[
] estimated glomerular filtration rate
(eGFR) < 60 ml/min/1.73m2. We defined diabetes as fasting glucose 7 mmol/L (126 mg/dL)
and/or use of medications for diabetes; and hypertension as systolic BP 140 or diastolic
90 mmHg and/or use of medications for hypertension.
Using means and standard deviations for continuous, or counts and percentages for
categorical variables, we described baseline characteristics stratified by sex and study type. We report
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Abbreviations: IDMS- isotope dilution mass spectrometry; CKD-chronic kidney disease; eGFR-estimated glomerular ®ltration rate.
raw, age-adjusted, and sex-stratified prevalence of overall CKD, eGFR < 60 ml/min/1.73m2,
and albuminuria in each study. We also examined prevalence of CKD according to the
following demographic and behavioral categories: income, education, physical activity, and fruit and
We adjusted the between-study prevalence difference in overall CKD, eGFR < 60 ml/min/
1.73m2, and albuminuria for age, waist-to-hip ratio, and diabetes, using a generalized linear
model with a log link and Binomial distribution (log-Binomial), or Poisson with robust
standard errors (modified Poisson model) if the log-Binomial model failed to converge[
persons with vascular disease can manifest hypertension and CKD, hypertension is also often
a consequence of CKD. We therefore did not adjust the prevalence difference in CKD for
prevalence of hypertension in the two studies.
Since overall missingness in the CARRS analytic study was approximately 20%, we
performed multiple imputation for missing covariates[
]. We assumed data to be missing at
random and used the Fully Conditioning Specification[
] approach to impute 20 full datasets,
stratified by sex. The MASALA study had only two missing observations; we thus performed a
complete case analysis for this study.
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In the participants with CKD in the two studies, we describe differences in prevalence of
risk factors associated with progression to ESRD and/or cardiovascular events in the two
studies. Further, we estimate the relative likelihood of an important clinical outcomeÐi.e., ESRD
or death due to kidney diseaseÐamong participants with diabetes and CKD in CARRS versus
MASALA. We used recently described five-year event rates from the standard arm of the
multi-country Action in Diabetes and Vascular Disease: Preterax and Diamicron MR
Controlled Evaluation (ADVANCE) study[
]. We obtained these event rates stratified according
to A1c category (<8 versus 8%), and multiplied the proportion of CKD participants falling
in the these two A1c categories with the respective events rates to estimate a relative risk in
CARRS versus MASALA. We used SAS, version 9.4 (SAS Institute, Inc., Cary, NC) or Stata
version 13.1 (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX:
StataCorp LP.) to perform all analyses.
Prevalence of CKD
Raw and age-adjusted prevalence of overall CKD was similar among men in CARRS and
MASALA, but substantially higher among women in MASALA compared with women in
CARRS (Table 3). Prevalence increased with age in both studies, and for both sexes (See
Table B in S2 File for age- and sex- stratified CKD prevalence). Overall, there was a
modestly higher prevalence of CKD in MASALA (14.0% [95% CI 11.8±16.3]) than in CARRS
(10.8% [95% CI 10.0±11.6]).
Investigating albuminuria further we found that while the prevalence of albuminuria was
higher in MASALA than in CARRS, the severity of albuminuria was higher in CARRS:
logmean albuminuria value was 4.5 ± 1.0 versus 4.1 ± 0.8 (p value = 0.01) among women in
CARRS and MASALA respectively, and 4.6 ± 1.2 versus 4.2 ± 0.7 (p value < 0.001) among
men in CARRS and MASALA (See Figures C-E in S1 File for albuminuria distribution and
Table C in S2 File for albuminuria categories). Odds of albuminuria did not differ by meat
intake status in either study (data not shown).
For both men and women, prevalence of CKD was higher in the highest tertile of income in
CARRS, but lower in MASALA when compared with participants in the lower tertiles of
income (Fig 1A and 1B). For other potential correlates such as physical activity, diabetes, and
hypertension, CARRS and MASALA study participants had similar directions of associations
with CKD. Women in MASALA had higher prevalence of CKD than women in CARRS across
Adjusted prevalence difference in CKD
We examined the prevalence difference in CKD after adjusting for diabetes, waist-to-height
ratio, and the residual effects of age (Fig 2A and 2B). Adjustment for these covariates led to a
slight attenuation in the magnitude of the CKD prevalence difference between MASALA and
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Data are expressed as mean (standard deviation), or number (percent in each group).
*Current tobacco use is de®ned as any cigarette use in the past 12 months.
¶Waist-to-height ratio > 0.5 is de®ned as abnormal
²Blood pressure and laboratory values report measured results regardless of self-reported disease status.
#Diabetes is de®ned as fasting glucose 7 mmol/L (126 mg/dL) and/or use of medications for diabetes.
kHypertension is de®ned as systolic BP 140 or diastolic 90 mmHg and/or use of medications for hypertension.
6 / 14
CARRS for both men and women. Nonetheless, the main findings remained unchanged. Men
in the two studies had similar prevalence of CKD, with albuminuria prevalence higher in
MASALA and eGFR < 60 ml/min/1.73m2 prevalence higher in CARRS. Women in MASALA
had a substantially higher prevalence of overall CKD and albuminuria than women in CARRS,
but the prevalence of eGFR < 60 ml/min/1.73m2 was slightly higher in women in CARRS.
In sensitivity analyses adjustment for hypertension status led to a further slight attenuation
of the prevalence difference between women (Table D in S2 File). Since income had a
differential relationship with CKD in the two studies, we performed stratified analyses further
adjusting for income and education. Among participants in the top tertile of income, men in
MASALA seemed to have slightly lower CKD prevalence, whereas women in MASALA
continued to demonstrate a higher CKD prevalence compared with counterparts in CARRS.
Fig 1. Prevalence of CKD according to demographic correlates in (A) men and (B) women In MASALA,
men with income in the lower tertiles had higher CKD prevalence than men with income in the top tertile. In
CARRS, men with no college education had higher CKD prevalence than men with college education. Across
studies, men with income in the lower tertiles in CARRS had higher CKD prevalence than men with income in
the lower tertiles in the MASALA. Women in the MASALA study had significantly higher prevalence of CKD
across nearly all demographic correlates compared with women in CARRS. * denotes statistically significant
difference within each study, # denotes statistically significant difference between studies.
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Fig 2. Prevalence difference in CKD in the MASALA study from the CARRS study (A) men and (B)
women. We present prevalence difference in CKD 1. Unadjusted, 2. Adjusted for age, and 3. Adjusted for
age, waist-to-height ratio, and diabetes. Prevalence difference in overall CKD and albuminuria among men in
CARRS and MASALA was negligible in all three models; prevalence of eGFR < 60 ml/min/1.73m2 was slightly
higher in men in CARRS. Unadjusted prevalence in overall CKD and albuminuria among women in MASALA
was 11.1% and 11.8% higher respectively compared with CARRS; adjusting for diabetes and waist-to-height
ratio did not attenuate this prevalence difference.
Risk factor management in participants with CKD
Among participants identified to have CKD in the two studies, the prevalence of hypertension
was similar and the prevalence of diabetes was lower in the MASALA than in the CARRS
study (Fig 3). Fewer participants in CARRS with these conditions were treated with
medications and fewer had evidence of meeting targets such as hemoglobin A1c < 7.0 among those
with diabetes (4% in CARRS versus 51% in MASALA) or blood pressure < 140/90 mmHg (7%
in CARRS versus 59% in MASALA) among those with hypertension. In sensitivity analyses,
we restricted this comparison to patients with a college degree or more, or to patients in the
top tertile of income and found that while the likelihood of meeting targets went up in both
groups, the gap between CARRS and MASALA participants in meeting targets remained large.
For example, among those with diabetes and CKD in the top income tertile, 9% of CARRS
participants had A1c < 7.0 compared with 63% in MASALA.
Since event rates for ESRD and/or death due to kidney disease are more than two-times
higher among those with poor glycemic control ( 8%) and CKD, CARRS participants
with diabetes and CKD are estimated to have 40% higher risk for experiencing this combined
outcome (relative risk 1.4, 95% CI: 0.8±2.6).
Behavioral characteristics known to attenuate risk for progression of CKD (e.g., physical
activity and abstaining from tobacco use) and/or associated cardiovascular events (e.g., fruit
and vegetable intake) were also more likely to be suboptimal in the CARRS than in MASALA
study. Awareness of presence of CKD was low in both studies.
Our study finds that the overall age-adjusted prevalence of CKD in Indians living in Indian
cities approaches that of Indians living in U.S. cities. Men in particular provided the strongest
evidence for a change in the trend that migration to HIC results in a dramatic increase in risk
for cardio-metabolic diseases. Furthermore, compared with counterparts living in the U.S.,
those with CKD living in urban India have more severe CKD and worse risk factor profilesÐ
e.g., higher likelihood of uncontrolled A1c or untreated hypertensionÐrendering them
vulnerable to experiencing more cardiovascular events and rapid kidney disease progression.
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Fig 3. Prevalence of risk factors for adverse events, and evidence of their management among participants with CKD. Of the
558 and 122 participants with CKD in CARRS and MASALA respectively, 430 (77%) and 119 (98%) had complete data on prevalence
of risk factors for progression of CKD and/or cardiovascular events. While 43% of participants with CKD in CARRS had diabetes, only
17% were on medications and only 2% (i.e., 4% of those with CKD and diabetes) had A1c < 7.0.
Women participating in the MASALA study had a substantially higher prevalence of
albuminuria without reduction in eGFR than women participating in CARRS. The small
prevalence difference in overall CKD between the two studies was driven in its entirety by a
substantially higher prevalence of albuminuria without a reduction in eGFR among women
participating in MASALA. Counter-intuitively, women in MASALA had similar prevalence of
hypertension, and lower prevalence of diabetes. They also attained higher educational status,
performed more physical activity, and consumed more fruits and vegetables than women in
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CARRS. Odds of albuminuria did not vary by meat intake status in the two studies. Women in
MASALA did have higher prevalence of abnormal waist-to-height ratio compared with
women in CARRS. Studies have linked central obesity to the presence[
] and severity[
albuminuria. In 205 South Asian adults without diabetes, the odds of albuminuria were 4-fold
higher in the group with highest waist-to-hip ratios, despite accounting for age, smoking
status, and blood pressure[
]. However, in our study, the albuminuria prevalence difference
among women persisted even after adjusting for age, diabetes, and waist-to-height ratio. Since
a single measure indicating presence of albuminuria strongly predicts 24 hour urine collection
], as well as future cardiovascular[
] and renal[
] outcomes, this finding deserves
Demographic correlates had a similar direction of association with prevalence of CKD in
CARRS and MASALA, with the notable exception of income. Compared with participants
in the highest income tertile, those with lower incomes were more likely to have CKD in
MASALA; the reverse was true for CARRS. A majority of studies in the U.S. and other HIC
have shown that higher income and educational status are associated with lower likelihood of
]. This pattern has not yet emerged in LMIC, where higher socioeconomic
groups experience higher metabolic risk. Lower socioeconomic groups are more likely facing
restricted caloric intake and/or physically active in their jobs, thereby counterbalancing other
high risk behaviors such as tobacco use and low fruit and vegetable intake[
Participants with CKD in the CARRS study demonstrated more severe kidney disease, and
most were not effectively managing risk factors. When restricting to participants with CKD
who also had a college degree or were in the top tertile of income±so a cohort more similar to
the MASALA participants±the proportion of patients on medications increased but a vast
majority (90% or more with diabetes or hypertension) were not meeting targets. Clearly a lack
of awareness of their condition[
] is a major reason, but even among those with a
diagnosis of diabetes or hypertension, there is little understanding of the need for regular medical
care. In a large survey performed in Chennai, only 40% of patients with diabetes knew that
their disease could lead to any organ complications[
]. Many experts also point to `clinical
inertia' in initiating and titrating medications[
]. In an international comparison of
physicians practices in managing diabetes, Indian physicians were among the most likely to delay
The lack of glycemic and blood pressure control has important implications for consequent
ESRD. Follow up data from the ADVANCE trialÐwhich recruited participants from India,
China, and Eastern European countries in addition to HICÐdemonstrate that hemoglobin
A1c can serve as a universal and significant predictor of ESRD. If we apply the event rates
from the standard arm follow up of this trial, CARRS participants with diabetes and CKD are
at 40% higher risk of experiencing ESRD or death due to kidney disease, since a much larger
proportion of them currently have hemoglobin A1c 8%. On the other hand, the ADVANCE
trial also proves that aggressively treating these risk factors can mitigate the most serious risks
associated with CKD in persons from a range of ethnicities, living in settings with a range of
healthcare resources [
Even among highly educated participants of the MASALA study (nearly all of whom avoid
smoking and eat fruits and vegetables regularly), we identified significant gaps in meeting
targets for diabetes or hypertension management in the participants with CKD. Similar gaps are
noted in the rest of the U.S. Using data from the 2005±2010 NHANES, the United States Renal
Data System reports that 48% of participants with CKD and diabetes had A1c < 7.0%; 51%
meet this target in MASALA[
]. About a third of participants with CKD in our study and in
NHANES 2005±2010 [
] have been prescribed angiotensin converting enzyme inhibitors or
angiotensin II receptor blockers.
10 / 14
Our study has several strengths. First, since a majority of participants in the MASALA
study were born in India, we were able to test the impact of ªresidenceº (i.e., U.S. metropolitan
versus Indian metropolitan areas) in genetically similar populations. Second, both studies used
standardized and comparable methodologies for laboratory, blood pressure, and
anthropometric ascertainment. Because both albuminuria and IDMS-standardized serum creatinine
were measured in the studies, we were able to use the most widely-accepted definition of CKD.
Detailed ascertainment of medication use allowed us to compare management of risk factors
among participants with CKD.
Limitations of our study include the different eligibility criteria and sampling techniques
used in CARRS and MASALA, and while we attempted to select a subset of CARRS cohort to
match MASALA entry criteria, important demographic differences in the two studies'
participants remain a source of bias. Most strikingly and as reflective of South Asian immigrants to
the U.S., the MASALA participants attained a much higher level of education than CARRS
participants. Serum creatinine was also measured via two different assays in the two studies,
but the two have been shown to have excellent agreement[
] and were calibrated against the
same standard (IDMS)[
], further minimizing inter-assay variation. Both studies only assessed
serum creatinine and urine albumin to creatinine at a single time point, and both may
therefore be over-estimating the prevalence of CKD since we cannot assess for persistence of
abnormal results. Since we studied only urban populations, we cannot generalize to the entire
populations of Indians living in either region. Finally, the overall nature of our cross-sectional
analyses is descriptive, without ability to draw causal inferences.
In conclusion, the prevalence of CKD in Indians living in Indian and U.S. cities is similar.
When we compare the risk profile of individuals with CKD, it is evident that those living in
Indian cities are substantially more likely to face worse outcomes. As more and more people
living in LMIC move to urban settings, their likelihood of disease may be similar, but likelihood of
receiving effective treatment is much lower than counterparts living in HIC. Focused and
contextually-appropriate programs targeting aggressive metabolic control can help close these gaps.
S1 File. Figures A-B: Study flowcharts demonstrating creation of analytic group. Figures C-E:
Distribution of log-albumin to creatinine ratio in CARRS versus MASALA participants with
S2 File. Table A. Age and education in participants with and without available information on
albuminuria and serum creatinine in the CARRS study. Table B. Age-stratified CKD
prevalence in CARRS and MASALA studies. Table C: Albuminuria in the CARRS and MASALA
studies. Table D: CKD prevalence (%) difference, after adjustment.
Conceptualization: SA AK MA VN DP GMC.
Data curation: DK KS PG.
Formal analysis: MMR YZ.
Funding acquisition: SA AK NK DP NT MA VN.
Investigation: RS RG AV RP VM.
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Methodology: RG RS DK MMR.
Project administration: RS AK NK.
Software: YZ PG KS.
Supervision: AK NK DP NT MA VN GMC.
Validation: MMR YZ.
Visualization: MMR YZ SA.
Writing ± original draft: SA.
Writing ± review & editing: SA MA VN GMC.
12 / 14
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