title: Dietary habits, poverty, and chronic kidney disease in an urban population.
abstract: BACKGROUND
  Poverty is associated with chronic kidney disease (CKD) in the United States and worldwide. Poor dietary habits may contribute to this disparity.
  
  
  METHODS
  Cross-sectional study.
  
  
  METHODS
  A total of 2,058 community-dwelling adults aged 30 to 64 years residing in Baltimore City, Maryland.
  
  
  METHODS
  Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet. DASH scoring based on 9 target nutrients (total fat, saturated fat, protein, fiber, cholesterol, calcium, magnesium, sodium, and potassium); adherence defined as score ≥4.5 of maximum possible score of 9. Poverty (self-reported household income <125% of 2004 Department of Health and Human Services guideline) and nonpoverty (≥125% of guideline).
  
  
  METHODS
  CKD defined as estimated glomerular filtration rate <60 mL/minute/1.73 m(2) (CKD epidemiology collaboration equation). Multivariable logistic regression was used to calculate adjusted odds ratios (AORs) for relation of DASH score tertile and CKD, stratified by poverty status.
  
  
  RESULTS
  Among 2,058 participants (mean age 48 years; 57% black; 44% male; 42% with poverty), median DASH score was low, 1.5 (interquartile range, 1-2.5). Only 5.4% were adherent. Poverty, male sex, black race, and smoking were more prevalent among the lower DASH score tertiles, whereas higher education and regular health care were more prevalent among the highest DASH score tertile (P < .05 for all). Fiber, calcium, magnesium, and potassium intake were lower, and cholesterol higher, among the poverty compared with nonpoverty group (P < .05 for all), with no difference in sodium intake. A total of 5.6% of the poverty and 3.8% of the nonpoverty group had CKD (P = .05). The lowest DASH tertile (compared with the highest) was associated with more CKD among the poverty (AOR 3.15, 95% confidence interval 1.51-6.56), but not among the nonpoverty group (AOR 0.73, 95% confidence interval 0.37-1.43; P interaction = .001).
  
  
  CONCLUSIONS
  Poor dietary habits are strongly associated with CKD among the urban poor and may represent a target for interventions aimed at reducing disparities in CKD.
authors.affiliation: Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland. Electronic address: dcrews1@jhmi.edu.
authors.forename: Deidra C
authors.initials: DC
authors.lastname: Crews
authors.affiliation: Department of Behavioral Health and Nutrition, University of Delaware, Newark, Delaware.
authors.forename: Marie Fanelli
authors.initials: MF
authors.lastname: Kuczmarski
authors.affiliation: Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors.forename: Edgar R
authors.initials: ER
authors.lastname: Miller
authors.affiliation: Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
authors.forename: Alan B
authors.initials: AB
authors.lastname: Zonderman
authors.affiliation: Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
authors.forename: Michele K
authors.initials: MK
authors.lastname: Evans
authors.affiliation: Department of Medicine, San Francisco General Hospital, University of California at San Francisco, San Francisco, California.
authors.forename: Neil R
authors.initials: NR
authors.lastname: Powe
mesh_terms: D000328:Adult; D015142:Baltimore / Q000453:epidemiology; D003430:Cross-Sectional Studies; D004032:Diet / Q000379:methods* / Q000706:statistics & numerical data; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys / Q000706:statistics & numerical data*; D011203:Poverty / Q000706:statistics & numerical data*; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology*; D014505:Urban Population / Q000706:statistics & numerical data*