Tazeen H. Jafar

Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis.

BACKGROUND Substantial controversy surrounds the use of estimated glomerular filtration rate (eGFR) and albuminuria to define chronic kidney disease and assign its stages. We undertook a meta-analysis to assess the independent and combined associations of eGFR and albuminuria with mortality. METHODS In this collaborative meta-analysis of general population cohorts, we pooled standardised data for all-cause and cardiovascular mortality from studies containing at least 1000 participants and baseline information about eGFR and urine albumin concentrations. Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause and cardiovascular mortality associated with eGFR and albuminuria, adjusted for potential confounders. FINDINGS The analysis included 105,872 participants (730,577 person-years) from 14 studies with urine albumin-to-creatinine ratio (ACR) measurements and 1,128,310 participants (4,732,110 person-years) from seven studies with urine protein dipstick measurements. In studies with ACR measurements, risk of mortality was unrelated to eGFR between 75 mL/min/1.73 m(2) and 105 mL/min/1.73 m(2) and increased at lower eGFRs. Compared with eGFR 95 mL/min/1.73 m(2), adjusted HRs for all-cause mortality were 1.18 (95% CI 1.05-1.32) for eGFR 60 mL/min/1.73 m(2), 1.57 (1.39-1.78) for 45 mL/min/1.73 m(2), and 3.14 (2.39-4.13) for 15 mL/min/1.73 m(2). ACR was associated with risk of mortality linearly on the log-log scale without threshold effects. Compared with ACR 0.6 mg/mmol, adjusted HRs for all-cause mortality were 1.20 (1.15-1.26) for ACR 1.1 mg/mmol, 1.63 (1.50-1.77) for 3.4 mg/mmol, and 2.22 (1.97-2.51) for 33.9 mg/mmol. eGFR and ACR were multiplicatively associated with risk of mortality without evidence of interaction. Similar findings were recorded for cardiovascular mortality and in studies with dipstick measurements. INTERPRETATION eGFR less than 60 mL/min/1.73 m(2) and ACR 1.1 mg/mmol (10 mg/g) or more are independent predictors of mortality risk in the general population. This study provides quantitative data for use of both kidney measures for risk assessment and definition and staging of chronic kidney disease. FUNDING Kidney Disease: Improving Global Outcomes (KDIGO), US National Kidney Foundation, and Dutch Kidney Foundation.Background A comprehensive evaluation of the independent and combined associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality is required for assessment of the impact of kidney function on risk in the general population, with implications for improving the definition and staging of chronic kidney disease (CKD).

Progression of Chronic Kidney Disease: The Role of Blood Pressure Control, Proteinuria, and Angiotensin-Converting Enzyme Inhibition: A Patient-Level Meta-Analysis

Context Guidelines recommend a blood pressure of less than 130/80 mm Hg for patients with chronic kidney disease. Contribution This meta-analysis showed that systolic blood pressure and urinary protein excretion were related to the risk for renal disease progression in patients with nondiabetic kidney disease. Systolic pressures of 110 to 129 mm Hg were associated with the lowest risks. Higher risks with higher pressures were marked in patients with protein excretion greater than 1.0 g/d and were not apparent in those with lower urinary protein excretion. Implications In patients with urinary protein excretion greater than 1.0 g/d, systolic blood pressure of 110 to 129 mm Hg is associated with the lowest risk for progression of renal disease. The Editors Chronic kidney disease is a major public health problem in the United States. The prevalence of kidney failure (recorded as end-stage renal disease) has risen steadily since Medicare assumed funding for the condition in 1973. By 2010, it is estimated that the prevalence will be greater than 650 000 (1). The prevalence of earlier stages of chronic kidney disease is even higher. The Third National Health and Nutrition Examination Survey (NHANES III), conducted from 1988 to 1994, estimates that 5.6 million persons 17 years of age or older had decreased kidney function, as defined by an elevated serum creatinine concentration ( 141 mol/L [ 1.6 mg/dL] in men and 124 mol/L [ 1.4 mg/dL] in women) (2). Hypertension and proteinuria occur in most patients with chronic kidney disease and are risk factors for faster progression of kidney disease. Antihypertensive agents reduce blood pressure and urine protein excretion and slow the progression of kidney disease. The sixth report of the Joint National Committee for the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-VI) recommends a lower blood pressure goal for patients with decreased kidney function (<130/85 mm Hg if urine protein excretion is <1 g/d and <125/75 mm Hg if urine protein excretion is >1 g/d) than for patients without target organ damage (<140/90 mm Hg) (3). It is not known whether even lower blood pressure might provide additional benefit. On the other hand, there is concern about excessive lowering of blood pressure because it may be associated with a higher risk for cardiovascular disease (4, 5). Additional lowering of blood pressure might also have a detrimental effect on kidney disease. The recommendations in JNC-VI are based principally on the results of the Modification of Diet in Renal Disease (MDRD) Study (6, 7), a study of nondiabetic kidney disease that did not evaluate the effect of angiotensin-converting enzyme (ACE) inhibitors or angiotensin-receptor blockers. Since publication of the JNC-VI, other large studies and meta-analyses have shown that antihypertensive regimens containing ACE inhibitors or angiotensin-receptor blockers seem to be more effective than other regimens in slowing the progression of chronic kidney disease (8-17). In some studies, the beneficial effect of these agents seemed to be greater in patients with proteinuria (8-11, 13) and was mediated in part by their effects to lower blood pressure and urine protein excretion (13). Of these studies, only the African American Study of Kidney Disease and Hypertension (AASK) compared two levels of blood pressure in patients treated with an ACE inhibitor (11). In that study of patients with hypertensive nephrosclerosis, a type of kidney disease associated with low levels of proteinuria, a lower blood pressure goal did not reduce the risk for progression of kidney disease when compared with a usual blood pressure goal. However, the AASK does not address the relationships of blood pressure and urine protein excretion with the progression of kidney disease in patients with higher levels of urine protein excretion. We performed a patient-level meta-analysis using data from the ACE Inhibition in Progressive Renal Disease (AIPRD) Study Group database (13) to assess these relationships among patients with nondiabetic kidney disease across a wide range of urine protein excretion values during antihypertensive therapy with and without ACE inhibitors. Methods Study Design The AIPRD Study Group database includes 1860 patients with nondiabetic kidney disease enrolled in 11 randomized, controlled trials of ACE inhibitors to slow the progression of kidney disease. The database contains information on blood pressure, urine protein excretion, serum creatinine concentration, and onset of kidney failure during 22 610 visits. Inclusion and exclusion criteria, search strategies for identifying clinical trials, and details of database formulation have been previously described (13, 18). The AIPRD Study Group was formed in 1997. Briefly, we identified studies by searching the MEDLINE database for English-language reports evaluating the effect of ACE inhibitors or kidney disease in humans between 1977 (when ACE inhibitors were approved for trials in humans) and 1999 (when the database was closed). We included only randomized trials (with a minimum 1-year follow-up) that compared the effects of antihypertensive regimens that included ACE inhibitors with the effects of regimens that did not include ACE inhibitors. Hypertension or decreased kidney function was required for entry into all studies. Exclusion criteria common to all studies were acute kidney failure, treatment with immunosuppressive medications, clinically significant congestive heart failure, obstructive uropathy, renal artery stenosis, active systemic disease, type 1 diabetes mellitus, history of transplantation, history of allergy to ACE inhibitors, and pregnancy. The institutional review board at each participating center approved the study, and all patients gave informed consent. Patients were enrolled between March 1986 and April 1996. All patients were randomly assigned to antihypertensive regimens either with or without ACE inhibitors. The ACE inhibitors included captopril, enalapril, cilazapril, benazepril, and ramipril. Concomitant antihypertensive medications were used in both groups to achieve a target blood pressure less than 140/90 mm Hg in all studies. All patients were followed at least once every 3 months for the first year and at least once every 6 months thereafter. Justification for pooling the 11 clinical trials is based on the similarity of study designs and patient characteristics. Justification for pooling placebo-controlled and active-drugcontrolled trials is based on the presence of preexisting hypertension and the use of antihypertensive agents in most patients in the control groups in each clinical trial. Thus, the pooled analysis addresses the clinically relevant question of the relationship of the level of blood pressure and urine protein excretion with the kidney disease progression during antihypertensive therapy, either with or without ACE inhibitors. Definition and Ascertainment of Blood Pressure and Urine Protein Excretion Clinical trial protocols stipulated measurement of blood pressure more frequently than urine protein excretion. In our database, visit was defined as any contact with patients during which study-related information was recorded or clinical variables were measured. Blood pressure was recorded on the same day as the visit in 94% of the visits and within 3 months before the visit in 99% of the visits. Urine protein excretion was recorded on the same day as the visit in 62% of the visits and within 6 months before the visit in 97% of the visits. Blood pressure and urine protein excretion levels at follow-up visits are defined as the current levels. We used current as well as baseline levels as the variables of interest for these analyses because guidelines for blood pressure target current values (3) and our previous studies have demonstrated that the current level of urine protein excretion is a stronger predictor of kidney disease progression than is the baseline level (19). Blood pressure was measured by using a mercury sphygmomanometer in nine studies (8-10, 20-24; Brenner BM. Personal communication) (93% of visits) and calibrated automatic device in two studies (25, 26). Systolic and diastolic blood pressure were measured after 5 to 10 minutes of rest in the supine position in 10 studies (8-10, 20, 22-26; Brenner BM. Personal communication) and in the sitting position in 1 study (21). Urine protein excretion was reported as total urine protein excretion in a 24-hour urine sample in 10 studies (8-10, 20-22, 24-26; Brenner BM. Personal communication) (95% of visits). One study performed a dipstick assessment in an untimed urine sample and reported quantitative measurement only if the dipstick result was positive (23). For that study, all values of dipstick negative were assigned a value of 0.1 g/d. In all studies, results for urine protein excretion of 0.1 g/d or lower were also assigned a value of 0.1 g/d. Values greater than 0.1 g/d were recorded as the exact values reported in the study and rounded to the nearest 0.1 g/d. Outcomes Serum creatinine concentration was recorded on the same day as the visit in 78% of visits and within 3 months after the visit in 96% of the visits. The primary outcome for the pooled analysis was kidney disease progression, defined as a combined end point of a twofold increase (doubling) in serum creatinine concentration from baseline values or development of kidney failure, defined as the initiation of long-term dialysis therapy. Statistical Analyses We used S-Plus 2000 (Insightful Corp., Seattle, Washington) and SAS software, version 8.2 (SAS Institute, Inc., Cary, North Carolina), software programs for statistical analyses. Cox proportional-hazards regression analysis was performed to detect associations between the covariates and outcomes. Baseline patient characteristics were treatment assignment (ACE inhibitor vs. control, using the intention-to-treat principle), age (logarithmic

Angiotensin-Converting Enzyme Inhibitors and Progression of Nondiabetic Renal Disease: A Meta-Analysis of Patient-Level Data

Chronic renal disease is a major public health problem in the United States. According to the 1999 Annual Data Report of the U.S. Renal Data System, more than 357 000 people have end-stage renal disease (ESRD), and the annual cost of treatment with dialysis and renal transplantation exceeds

Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention

15.6 billion (1). Patients undergoing dialysis have reduced quality of life, a high morbidity rate, and an annual mortality rate of 20% to 25% (1). Identification of therapies to prevent ESRD is an important public health goal. Angiotensin-converting enzyme (ACE) inhibitors are highly effective in slowing the progression of renal disease due to type 1 diabetes (26), and evidence of their efficacy in type 2 diabetes is growing (712). However, although 14 randomized, controlled trials have been completed (1325; Brenner BM; Toto R. Personal communications), no consensus exists on the use of ACE inhibitors in nondiabetic renal disease (2628). In a previous meta-analysis of 11 randomized, controlled trials, we found that therapy with ACE inhibitors slowed the progression of nondiabetic renal disease (29). Since our meta-analysis was performed on group data rather than individual-patient data, we could not fully assess the relationship between the effect of ACE inhibitors and blood pressure, urinary protein excretion, or other patient characteristics (30). Thus, we could not determine whether an equal reduction in blood pressure or urinary protein excretion by using other antihypertensive agents would be as effective in slowing the progression of renal disease. Nor could we determine whether the baseline blood pressure, urinary protein excretion, or other patient characteristics modified the response to treatment. In the current report, we used pooled analysis of individual-patient data to answer these questions. We reasoned that the large number of patients in the pooled analysis would provide sufficient statistical power to detect relationships between patient characteristics and risk for progression of renal disease and interactions of patient characteristics with treatment effect. In principle, strong and consistent results from analysis of this large database would clarify the effects of ACE inhibitors for treatment of nondiabetic renal disease. Methods Study Design We obtained individual-patient data from nine published (1322) and two unpublished (Brenner BM; Toto R. Personal communications) randomized, controlled trials assessing the effects of ACE inhibitors on renal disease progression in predominantly nondiabetic patients. Search strategies used to identify clinical trials have been described elsewhere and are reviewed in Appendix 2. We included 11 randomized trials on progression of renal disease that compared the effects of antihypertensive regimens including ACE inhibitors to the effects of regimens without ACE inhibitors, with a follow-up of at least 1 year. In these studies, the institutional review board at each participating center approved the study, and all patients gave informed consent. Patients underwent randomization between March 1986 and April 1996. Hypertension or decreased renal function was required for entry into all studies. Exclusion criteria common to all studies were acute renal failure, treatment with immunosuppressive medications, clinically significant congestive heart failure, obstructive uropathy, renal artery stenosis, active systemic disease, insulin-dependent diabetes mellitus, history of transplantation, history of allergy to ACE inhibitors, and pregnancy. Table 1 shows characteristics of the patients in each study. Table 1. Study and Patient Characteristics in the Randomized, Controlled Trials Included in the Pooled Analysis Before randomization, patients already taking an ACE inhibitor were switched to alternative medications for at least 3 weeks. After randomization, the ACE inhibitor groups received enalapril in seven studies (1419; Brenner BM; Toto R. Personal communications) and captopril (13), benazepril (20), cilazapril (18), and ramipril (21, 22) in one study each. The control groups received placebo in five studies (1922; Brenner BM; Toto R. Personal communications), a specified medication in five studies (nifedipine in two studies [13, 17] and atenolol or acebutolol in three studies [15, 16, 18]), and no specified medication in one study (14). Other antihypertensive medications were used in both groups to reach the target blood pressure, which was less than 140/90 mm Hg in all studies. All patients were followed at least once every 6 months for the first year and at least once yearly thereafter. Blood pressure and laboratory variables were measured at each visit. Table 1 shows outcomes of each study. We pooled the 11 clinical trials on the basis of similarity of study designs and patient characteristics. In addition, the presence of preexisting hypertension and use of antihypertensive agents in most patients in the control groups in each clinical trial justified pooling data from placebo-controlled and active-controlled trials. Thus, the pooled analysis addresses the clinically relevant question of whether antihypertensive regimens including ACE inhibitors are more effective than anti-hypertensive regimens not including ACE inhibitors in slowing the progression of nondiabetic renal disease. Outcomes Two primary outcomes were defined: ESRD, defined as the initiation of long-term dialysis therapy, and a combined outcome of a twofold increase in serum creatinine concentration from baseline values or ESRD. Because ESRD is a clinically important outcome, we believed that definitive results of analyses using this outcome would be clinically relevant. However, because most chronic renal diseases progress slowly, few patients might reach this outcome during the relatively brief follow-up of these clinical trials, resulting in relatively low statistical power for these analyses. Doubling of baseline serum creatinine is a well-accepted surrogate outcome for progression of renal disease in studies of antihypertensive agents (2, 20) and would be expected to occur more frequently than ESRD, providing higher statistical power for analyses using this outcome. Doubling of baseline serum creatinine concentration was confirmed by repeated evaluation in only one study, which used this variable as the primary outcome. Therefore, we did not require confirmation of doubling for our analysis. Other outcomes included death and a composite outcome of ESRD and death. Withdrawal was defined as discontinuation of follow-up before the occurrence of an outcome or study end. Reasons for withdrawal were 1) nonfatal side effects possibly due to ACE inhibitors, including hyperkalemia, cough, angioedema, acute renal failure, or hypotension; 2) nonfatal cardiovascular disease events, including myo-cardial infarction, congestive heart failure, stroke, transient ischemic attack, or claudication; 3) other nonfatal events, such as malignant disease, pneumonia, cellulitis, headache, or gastrointestinal disturbance; and 4) other reasons, including loss to follow-up, protocol violation, or unknown. Statistical Analysis Five investigators participated in data cleaning. Summary tables were compiled from the individual-patient data from each study and checked against tables in published and unpublished reports. Discrepancies were resolved by contacting investigators at the clinical or data coordinating centers whenever possible. Because the studies followed different protocols, we had to standardize the variable definitions, follow-up intervals, and run-in periods; details of our approach are provided in Appendix 2. S-Plus (MathSoft, Inc., Seattle, Washington) and SAS (SAS Institute, Inc., Cary, North Carolina) software programs were used for all statistical analyses (31, 32). Univariate analysis was performed to detect associations between the covariates and outcomes. Baseline patient characteristics were treatment assignment (ACE inhibitor vs. control), age (logarithmic transformation), sex, ethnicity, systolic blood pressure, diastolic blood pressure, mean arterial pressure, serum creatinine concentration (reciprocal transformation), and urinary protein excretion. Study characteristics were blinding, type of antihypertensive regimen in the control group, planned duration of follow-up, whether dietary protein or sodium was restricted, and year of publication. Baseline patient characteristics and study characteristics were introduced as fixed covariates. Since renal biopsy was not performed in most cases and since criteria for classification of cause of renal disease were not defined, the cause of renal disease was not included as a variable in the analysis. Follow-up patient characteristics (blood pressure and urinary protein excretion) were adjusted as time-dependent covariates; the value recorded at the beginning of each time segment was used for that segment. This convention was used so that each outcome would be determined only by previous exposure. The intention-to-treat principle was followed for comparison of randomized groups. Cox proportional-hazards regression models were used to determine the effect of assignment to ACE inhibitors (treatment effect) and other covariates on risk for ESRD and the combined outcome (33, 34). Multivariable models were built by using candidate predictors that were associated with the outcome (P<0.2) in the univariate analysis. Each model was adjusted for study, but since some studies had no events, we could not include a dummy variable for each study. Rather, we adjusted models for studies that differed significantly from the rest (studies 2 [14], 5 [15], 10 [20], and 11 [21, 22]). We also performed tests for interactions between all covariates and treatment effect. All P values were based on two-sided tests, and significance was set at a P value less than 0.05. Results are expressed as relative risks with 95% CIs. Residual diagnostics were performed on these final models (33, 34)

Comparison of risk prediction using the CKD-EPI equation and the MDRD Study equation for estimated glomerular filtration rate

Since the first description of the association between chronic kidney disease and heart disease, many epidemiological studies have confirmed and extended this finding. As chronic kidney disease progresses, kidney-specific risk factors for cardiovascular events and disease come into play. As a result, the risk for cardiovascular disease is notably increased in individuals with chronic kidney disease. When adjusted for traditional cardiovascular risk factors, impaired kidney function and raised concentrations of albumin in urine increase the risk of cardiovascular disease by two to four times. Yet, cardiovascular disease is frequently underdiagnosed and undertreated in patients with chronic kidney disease. This group of patients should, therefore, be acknowledged as having high cardiovascular risk that needs particular medical attention at an individual level. This view should be incorporated in the development of guidelines and when defining research priorities. Here, we discuss the epidemiology and pathophysiological mechanisms of cardiovascular risk in patients with chronic kidney disease, and discuss methods of prevention.

Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci

CONTEXT The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS A meta-analysis of data from 1.1 million adults (aged ≥ 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS Estimated GFR was classified into 6 categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

Prevalence of overweight and obesity and their association with hypertension and diabetes mellitus in an Indo-Asian population.

We carried out a genome-wide association study of type-2 diabetes (T2D) in individuals of South Asian ancestry. Our discovery set included 5,561 individuals with T2D (cases) and 14,458 controls drawn from studies in London, Pakistan and Singapore. We identified 20 independent SNPs associated with T2D at P < 10−4 for testing in a replication sample of 13,170 cases and 25,398 controls, also all of South Asian ancestry. In the combined analysis, we identified common genetic variants at six loci (GRB14, ST6GAL1, VPS26A, HMG20A, AP3S2 and HNF4A) newly associated with T2D (P = 4.1 × 10−8 to P = 1.9 × 10−11). SNPs at GRB14 were also associated with insulin sensitivity (P = 5.0 × 10−4), and SNPs at ST6GAL1 and HNF4A were also associated with pancreatic beta-cell function (P = 0.02 and P = 0.001, respectively). Our findings provide additional insight into mechanisms underlying T2D and show the potential for new discovery from genetic association studies in South Asians, a population with increased susceptibility to T2D.

Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data

Background: The associations of body mass index (BMI) and chronic disease may differ between Indo-Asian and Western populations. We used Indo-Asian-specific definitions of overweight and obesity to determine the prevalence of these problems in Pakistan and studied the sensitivity and specificity of BMI cutoff values for an association with hypertension and diabetes mellitus. Methods: We analyzed data for 8972 people aged 15 years or more from the National Health Survey of Pakistan (1990–1994). People considered overweight or obese were those with a BMI of 23 kg/m2 or greater, and those considered obese as having a BMI of 27 kg/m2 or greater. We built multivariable models and performed logistic regression analysis. Results: The prevalence of overweight and obesity, weighted to the general Pakistani population, was 25.0% (95% confidence interval [CI] 21.8%–28.2%). The prevalence of obesity was 10.3% (95% CI 7.0%–13.2%). The factors independently and significantly associated with overweight and obesity included greater age, being female, urban residence, being literate, and having a high (v. low) economic status and a high (v. low) intake of meat. With receiver operating characteristic curves, we found that the use of even lower BMI cutoff values (21.2 and 22.1 kg/m2 for men and 21.2 and 22.9 kg/m2 for women) than those recommended for an Indo-Asian population yielded the optimal areas under the curve for an association with hypertension and diabetes, respectively. Interpretation: A quarter of the population of Pakistan would be classified as overweight or obese with the use of Indo-Asian-specific BMI cutoff values. Optimal identification of those at risk of hypertension and diabetes and healthy targets may require the use of even lower BMI cutoff values than those already proposed for an Indo-Asian population.

Ethnic subgroup differences in hypertension in Pakistan

Background The utility of estimated glomerular filtration rate (eGFR) and albuminuria for cardiovascular prediction is controversial. Methods We meta-analyzed individual-level data from 24 cohorts (with a median follow-up time longer than 4 years, varying from 4.2 to 19.0 years) in the Chronic Kidney Disease Prognosis Consortium (637,315 participants without a history of cardiovascular disease) and assessed C-statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in 5-year timeframe, contrasting prediction models consisting of traditional risk factors with and without creatinine-based eGFR and/or albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria). Findings The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR and more evident for cardiovascular mortality (c-statistic difference 0.0139 [95%CI 0.0105–0.0174] and 0.0065 [0.0042–0.0088], respectively) and heart failure (0.0196 [0.0108–0.0284] and 0.0109 [0.0059–0.0159]) than for coronary disease (0.0048 [0.0029–0.0067] and 0.0036 [0.0019–0.0054]) and stroke (0.0105 [0.0058–0.0151] and 0.0036 [0.0004–0.0069]). Dipstick proteinuria demonstrated smaller improvement than ACR. The discrimination improvement with kidney measures was especially evident in individuals with diabetes or hypertension but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these conditions. In participants with chronic kidney disease (CKD), the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the c-statistic for cardiovascular mortality declined by 0.023 [0.016–0.030] vs. <0.007 when omitting eGFR and ACR vs. any single modifiable traditional predictors, respectively. Interpretation Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when they are already assessed for clinical purpose and/or cardiovascular mortality and heart failure are the outcomes of interest (e.g., the European guidelines on cardiovascular prevention). ACR may have particularly broad implications for cardiovascular prediction. In CKD populations, the simultaneous assessment of eGFR and ACR will facilitate improved cardiovascular risk classification, supporting current CKD guidelines. Funding US National Kidney Foundation and NIDDKBACKGROUND The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach. METHODS We meta-analysed individual-level data for 637 315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4·2-19·0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both. FINDINGS The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0·0139 [95% CI 0·0105-0·0174] for ACR and 0·0065 [0·0042-0·0088] for eGFR) and heart failure (0·0196 [0·0108-0·0284] and 0·0109 [0·0059-0·0159]) than for coronary disease (0·0048 [0·0029-0·0067] and 0·0036 [0·0019-0·0054]) and stroke (0·0105 [0·0058-0·0151] and 0·0036 [0·0004-0·0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0·0227 (0·0158-0·0296) after omission of eGFR and ACR compared with less than 0·007 for any single modifiable traditional predictor. INTERPRETATION Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population. FUNDING US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.

Children in South Asia Have Higher Body Mass–Adjusted Blood Pressure Levels Than White Children in the United States A Comparative Study

Objective Cardiovascular risks are globally elevated in South Asians, but this masks important ethnic subgroup differences in risk factors, such as hypertension, which have not been fully explored. We conducted this study to explore the variations in hypertension within ethnic subgroups among South Asians. Design Cross-sectional survey [National Health Survey of Pakistan (NHSP) (1990–1994)]. Setting Population based. Participants A total of 9442 individuals aged 15 years or over. Methods Data on sociodemographic and clinical variables were collected. Distinct ethnic subgroups – Muhajir, Punjabi, Sindhi, Pashtun and Baluchi – were defined by mother tongue. Main outcome measure Hypertension defined as systolic blood pressure ⩾ 140 mmHg or diastolic blood pressure ⩾ 90 mmHg, or currently receiving antihypertensive therapy. Results The age-standardized prevalence of hypertension was highest among Baluchis (25.3% in men and 41.4% in women), then Pashtuns (23.7% in men and 28.4% in women), Muhajirs (24.1% in men and 24.6% in women), and lowest among Punjabis (17.3% in men and 16.4% in women) and Sindhis (19.0% in men and 9.9% in women) (P = 0.001). While hypertension was more prevalent in urban (22.7%) versus rural dwellers (18.1%) [odds ratio (OR) 1.34; 95% confidence interval (CI), 1.20, 1.49], this difference was no longer significant after adjusting for body mass and waist circumference (OR 1.03; 95% CI, 0.91, 1.16). However, ethnic differences persisted after adjusting for major sociodemographic, dietary and clinical risk factors (unadjusted OR for Baluchi versus Sindhi, 2.92; 95% CI, 2.20–3.89; adjusted OR, 2.71; 95% CI, 1.97–3.75). Conclusions A threefold difference in prevalence of hypertension exists between people of South Asian descent, which, unlike the urban/rural difference, cannot be accounted for by measured risk factors. Further study would provide valuable etiological and therapeutic clues.