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

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.

Income is a stronger predictor of mortality than education in a national sample of US adults.

Low socioeconomic status (SES) is associated with mortality in several populations. SES measures, such as education and income, may operate through different pathways. However, the independent effect of each measure mutually adjusting for the effect of other SES measures is not clear. The association between poverty-income ratio (PIR) and education and all-cause mortality among 15,646 adults, aged >20 years, who participated in the Third National Health and Nutrition Examination Survey in the USA, was examined. The lower PIR quartiles and less than high school education were positively associated with all-cause mortality in initial models adjusting for the demographic, lifestyle and clinical risk factors. After additional adjustment for education, the lower PIR quartiles were still significantly associated with all-cause mortality. The multivariable odds ratio (OR) [95% confidence interval (CI)] of all-cause mortality comparing the lowest to the highest quartile of PIR was 2.11 (1.52-2.95, p trend < or = 0.0001). In contrast, after additional adjustment for income, education was no longer associated with all-cause mortality [multivariable OR (95% CI) of all-cause mortality comparing less than high school to more than high school education was 1.05 (0.85-1.31, p trend=0.57)]. The results suggest that income may be a stronger predictor of mortality than education, and narrowing the income differentials may reduce the health disparities.

Relationship between body mass index and high cystatin levels among US adults.

High cystatin C levels among patients without clinically recognized chronic kidney disease (CKD) may identify patients who are at preclinical stages of CKD. Higher body mass index (BMI) has been found to be associated with increased risk of CKD. However, the association between BMI and high cystatin C levels is not clear. The authors examined participants older than 20 years from the National Health and Nutrition Examination Survey 1999 to 2002 (N=2583, 50.2% women). BMI was categorized as <25 kg/m(2), 25-29.9 kg/m(2), and ≥30 kg/m(2) . Main outcome was high cystatin C (>1 mg/dL) among patients without clinically recognized CKD (estimated glomerular filtration rate <60 mL/min/1.73 m(2) or microalbuminuria). Higher BMI was positively associated with high cystatin C, independent of age, sex, race-ethnicity, education, smoking, alcohol intake, cholesterol, and C-reactive protein levels. Compared with patients with BMI <25 kg/m(2) (referent), the multivariable odds ratio (95% confidence interval) of high cystatin C was 2.53 (1.79-3.58) (P trend <.0001 among patients with BMI ≥30 kg/m(2)). The association between BMI and high cystatin C persisted in subgroup analyses by sex, race-ethnicity, and among those without diabetes or hypertension. Among US adults without clinically recognized CKD, higher BMI levels were independently associated with high cystatin C levels.

Socioeconomic status, self-rated health, and mortality in a multiethnic sample of US adults.

OBJECTIVE: To examine the association between socioeconomic status (SES), self-rated health (SRH), and mortality separately by race-ethnicity in a nationally representative sample of US adults. METHODS: We analyzed data from 16 716 adult women and men who were followed up for mortality for up to 12 years as part of the third National Health and Nutrition Examination survey (NHANES III). Poverty-income ratio (PIR) and education were assessed as measures of SES. All-cause mortality (n = 2850) was recorded from the NHANES III linked mortality file. RESULTS: Lower PIR was associated with mortality after adjustment for lifestyle, clinical risk factors, and SRH in all racial-ethnic groups (P-trend <0.005). In contrast, after adjusting for lifestyle and clinical risk factors, lower education was not associated with all-cause mortality in non-Hispanic whites (P-trend = 0.16), whereas the association remained significant after adjustment for SRH and lifestyle and clinical risk factors in other race-ethnicities (P-trend = 0.005; P-interaction between education categories and race-ethnicity was 0.02). CONCLUSIONS: Our results suggest that lower PIR was associated with mortality in all racial-ethnic groups. In contrast, lower education was significantly associated with mortality only in racial-ethnic groups other than non-Hispanic whites. Our results indicate that, beyond lifestyle and clinical risk factors, adjusting for SRH resulted in only a modest change in the association of SES and mortality.

Self-rated health, associated factors and diseases: a community-based cross-sectional study of Singaporean adults aged 40 years and above.

INTRODUCTION: Subjective indicators of health like self-rated health (SRH) have been shown to be a predictor of mortality and morbidity. We determined the prevalence of poor SRH in Singapore and its association with various lifestyle and socioeconomic factors and disease states. MATERIALS AND METHODS: Cross-sectional survey by interviewer-administered questionnaire of participants aged 40 years and above. SRH was assessed from a standard question and categorised into poor, fair, good or excellent. Lifestyle factors, socioeconomic factors and presence of disease states were also assessed. RESULTS: Out of 409 participants, 27.6% rated their health as poor or fair, 53.1% as good and 19.3% as excellent. Smaller housing-type (PRR: 1.64, 95% CI: 1.10- 2.44) and lack of exercise (PRR: 1.54, 95% CI: 1.06-2.22) were found to be associated with poor SRH. Presence of chronic diseases such as coronary artery disease (PRR: 1.89, 95% CI: 1.13-3.17), diabetes mellitus (PRR: 1.85, 95% CI: 1.18-2.91), history of cancer (PRR: 2.15, 95% CI: 1.05-4.41) and depression (PRR: 1.73, 95% CI: 1.13-2.65) were associated with poor SRH. CONCLUSION: Prevalence and factors associated with poor SRH in Singapore was comparable to other developed countries. SRH is an important subjective outcome of health and has the potential for wider use in clinical practice in Singapore.

The association between socioeconomic status and overweight/obesity in a Malay population in Singapore.

In developed countries in the West, lower socioeconomic status (SES) is associated with a higher prevalence of overweight/obesity. The authors examined the association between SES defined by education and income and overweight/obesity in a population-based cohort of 2807 individuals of Malay ethnicity (age 40-80 years, 51% women) in Singapore. The prevalence of overweight/ obesity (body mass index > or =25 kg/m(2)) in men and women was 50.4% and 65.1%, respectively. In women, the prevalence of overweight/obesity increased with lower levels of education and income. Compared with the higher categories of SES, the odds ratio (95% confidence interval) of overweight/obesity in women was 1.42 (1.06-1.89) for education and 2.08 (1.33-3.26) for income. In contrast, in men, the prevalence of overweight/obesity decreased with lower levels of education and income (P interaction by gender <.05 for all SES variables). Lower SES was positively associated with overweight/obesity in Malay women, and the association was in the opposite direction in Malay men.