Dietary Phosphorus Intake and Mortality in Moderate CKD
Dietary Phosphorus Intake and Mortality in Moderate CKD
The NHANES is an ongoing series of the surveys of the non-institutionalized civilian population in the USA conducted by the National Center for Health Statistics. From 1988 to 1994, NHANES III, a cross-sectional survey of the US population was carried out. It used a complex, multistage sampling design to obtain a sample that is representative of the non-institutionalized civilian US population of early 1990s.
Briefly, participants provided informed consent and underwent a structured home interview conducted by trained personnel to ascertain self-reported medical history of conditions such as myocardial infarction, stroke, congestive heart failure and diabetes. This was followed by a physical examination, which included blood pressure measurement, extensive anthropometric and physiological assessments and blood draw for laboratory testing at the NHANES Mobile Examination Center. The time of the blood draw and the number of hours of fasting before the blood draw were recorded. As detailed below, during this visit, participants also underwent a detailed diet interview.
Serum creatinine, albumin, calcium and phosphorus were analyzed on a Hitachi 737 automated analyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN) using reagents from Boehringer Mannheim Diagnostics. Serum creatinine measurements obtained using a kinetic rate Jaffe method in NHANES III were recalibrated to standardized creatinine measurements obtained at the Cleveland Clinic Research Laboratory (Cleveland, OH) as standard creatinine = −0.184 + 0.960 × NHANES III measured serum creatinine. GFR was estimated as 175 × (standardized serum creatinine) × (age) × 0.742 (if the individual is woman) × 1.212 (if the individual is African-American). CKD was defined as GFR <60 mL/min/1.73 m.
Details about dietary assessment methodology have been published elsewhere. A computer-based interview system developed by the University of Minnesota's Nutrition Coordinating Center (Regents of the University of Minnesota) was used to conduct a 24-h dietary recall. The 24-h dietary recall was conducted by trained interviewers. The US Department of Agriculture's Survey Nutrient Data Base was used to calculate macro- and micronutrient content of the foods consumed during the 24-h recall period for each respondent.
A trained technician carried out anthropometric measurements, while another trained technician assisted and recorded the measures. Weight was measured to the nearest 0.01 kg on an electronic scale. Standing height was measured to the nearest 0.1 cm with a stadiometer. Bioimpedance analysis (BIA) model 1990B (Valhalla Scientific, San Diego, CA) was used for the measurement of whole body electrical resistance and impedance. A standardized protocol for BIA procedure was carried out by trained observers and physicians in a standardized environment. Lean body mass (LBM) was estimated from prediction equations that were validated and cross-validated for men and women separately and for blacks and whites between the ages of 12 and 94 years. [men: LBM (kg) = −10.68 + (0.65 × S/resistance) + (0.26 × weight) + (0.02 × resistance) and women: LBM (kg) = −9.53 + (0.69 × S/resistance)+ (0.17 × weight) + (0.02 × resistance) where S/resistance is stature squared divided by resistance (cm/Ω)].
The National Center for Health Statistics created an NHANES III Linked Mortality File that contains mortality follow-up data from the date of NHANES III survey participation (1988–1994) through December 31, 2000. This information was based upon the results from a probabilistic match between NHANES III and National Death Index death certificate records.
NHANES III utilized a complex multistage probability sample design. Several aspects of the NHANES design must be taken into account in data analysis, including the sampling weights and clustered sampling. We used the svy suite of commands in Stata 11 (Stata 11, College station, TX) and followed the analytical guidelines for NHANES data proposed by the Centers for Disease Control. The svy commands in Stata accounts for the elements of NHANES sampling design to calculate the expected means and proportions of the entire US non-institutionalized civilian CKD population, which are presented with the estimated values and with associated 95% confidence intervals.
Using gender-specific tertiles, unadjusted associations of dietary phosphorus intake with baseline characteristics including dietary variables (calorie, protein, calcium and magnesium intake), nutritional variables (serum albumin and LBM) and serum calcium, phosphorus and calcium–phosphorus product were examined using chi-square contingency table analysis for categorical variables and analysis of variance for continuous variables.
In a multivariable linear regression model, the association of dietary phosphorus with serum phosphorus was examined adjusted for demographics (age, gender and race), dietary variables (calorie intake and percent calories from protein), time of the day (morning: 7:00–11:59 AM, afternoon: 12:00–4:49 PM and evening: 5:00–11:00 PM) when the blood was drawn and the hours of fasting before the blood was drawn.
The unadjusted association of dietary phosphorus intake with mortality was first examined in a Cox proportional hazards regression model without covariate adjustment. Next, this model was adjusted for age, gender and race to examine the extent to which demographic variables confound this association. A third Cox regression model was performed with further covariate adjustment for comorbid conditions (history of myocardial infarction, stroke, congestive heart failure, cancer and diabetes), lifestyle factors (smoking, alcohol use and physical activity), dietary variables (calorie intake and percent calories from protein) and estimated glomerular filtration rate (eGFR). Finally, as higher phosphorus intake might be associated with better nutritional status, the effects of further adjusting for nutritional variables [serum albumin, body mass index (BMI) and LBM] were examined in a fourth Cox regression model.
The assumption of proportional hazards was examined by comparing the logarithm of the hazard ratio (HR) for each predictor variable in the first 3 years of follow-up to the logarithm of the HR of the predictor variables after Year 3. No models showed proportional hazards assumption violations with respect to dietary phosphorus intake.
The factors gender and stroke exhibited a significant deviation from proportional hazards (P < 0.05) in at least one of the models. Hence, rather than including these factors as covariates, each of the Cox regressions was stratified by each of these factors to allow separate baseline hazard functions within each stratum. In addition, quadratic terms were tested for each continuous covariate to test for the presence of nonlinear effects of that covariate. No quadratic terms were statistically significant.
Similar analyses were performed treating dietary phosphorus intake as a categorical variable with the lowest dietary phosphorus intake as the reference group.
Methods
Study Population and Baseline Data
The NHANES is an ongoing series of the surveys of the non-institutionalized civilian population in the USA conducted by the National Center for Health Statistics. From 1988 to 1994, NHANES III, a cross-sectional survey of the US population was carried out. It used a complex, multistage sampling design to obtain a sample that is representative of the non-institutionalized civilian US population of early 1990s.
Briefly, participants provided informed consent and underwent a structured home interview conducted by trained personnel to ascertain self-reported medical history of conditions such as myocardial infarction, stroke, congestive heart failure and diabetes. This was followed by a physical examination, which included blood pressure measurement, extensive anthropometric and physiological assessments and blood draw for laboratory testing at the NHANES Mobile Examination Center. The time of the blood draw and the number of hours of fasting before the blood draw were recorded. As detailed below, during this visit, participants also underwent a detailed diet interview.
Serum creatinine, albumin, calcium and phosphorus were analyzed on a Hitachi 737 automated analyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN) using reagents from Boehringer Mannheim Diagnostics. Serum creatinine measurements obtained using a kinetic rate Jaffe method in NHANES III were recalibrated to standardized creatinine measurements obtained at the Cleveland Clinic Research Laboratory (Cleveland, OH) as standard creatinine = −0.184 + 0.960 × NHANES III measured serum creatinine. GFR was estimated as 175 × (standardized serum creatinine) × (age) × 0.742 (if the individual is woman) × 1.212 (if the individual is African-American). CKD was defined as GFR <60 mL/min/1.73 m.
Dietary Assessment
Details about dietary assessment methodology have been published elsewhere. A computer-based interview system developed by the University of Minnesota's Nutrition Coordinating Center (Regents of the University of Minnesota) was used to conduct a 24-h dietary recall. The 24-h dietary recall was conducted by trained interviewers. The US Department of Agriculture's Survey Nutrient Data Base was used to calculate macro- and micronutrient content of the foods consumed during the 24-h recall period for each respondent.
Nutritional Assessment
A trained technician carried out anthropometric measurements, while another trained technician assisted and recorded the measures. Weight was measured to the nearest 0.01 kg on an electronic scale. Standing height was measured to the nearest 0.1 cm with a stadiometer. Bioimpedance analysis (BIA) model 1990B (Valhalla Scientific, San Diego, CA) was used for the measurement of whole body electrical resistance and impedance. A standardized protocol for BIA procedure was carried out by trained observers and physicians in a standardized environment. Lean body mass (LBM) was estimated from prediction equations that were validated and cross-validated for men and women separately and for blacks and whites between the ages of 12 and 94 years. [men: LBM (kg) = −10.68 + (0.65 × S/resistance) + (0.26 × weight) + (0.02 × resistance) and women: LBM (kg) = −9.53 + (0.69 × S/resistance)+ (0.17 × weight) + (0.02 × resistance) where S/resistance is stature squared divided by resistance (cm/Ω)].
Follow-up Data
The National Center for Health Statistics created an NHANES III Linked Mortality File that contains mortality follow-up data from the date of NHANES III survey participation (1988–1994) through December 31, 2000. This information was based upon the results from a probabilistic match between NHANES III and National Death Index death certificate records.
Statistical Analyses
NHANES III utilized a complex multistage probability sample design. Several aspects of the NHANES design must be taken into account in data analysis, including the sampling weights and clustered sampling. We used the svy suite of commands in Stata 11 (Stata 11, College station, TX) and followed the analytical guidelines for NHANES data proposed by the Centers for Disease Control. The svy commands in Stata accounts for the elements of NHANES sampling design to calculate the expected means and proportions of the entire US non-institutionalized civilian CKD population, which are presented with the estimated values and with associated 95% confidence intervals.
Using gender-specific tertiles, unadjusted associations of dietary phosphorus intake with baseline characteristics including dietary variables (calorie, protein, calcium and magnesium intake), nutritional variables (serum albumin and LBM) and serum calcium, phosphorus and calcium–phosphorus product were examined using chi-square contingency table analysis for categorical variables and analysis of variance for continuous variables.
In a multivariable linear regression model, the association of dietary phosphorus with serum phosphorus was examined adjusted for demographics (age, gender and race), dietary variables (calorie intake and percent calories from protein), time of the day (morning: 7:00–11:59 AM, afternoon: 12:00–4:49 PM and evening: 5:00–11:00 PM) when the blood was drawn and the hours of fasting before the blood was drawn.
Survival Analyses
The unadjusted association of dietary phosphorus intake with mortality was first examined in a Cox proportional hazards regression model without covariate adjustment. Next, this model was adjusted for age, gender and race to examine the extent to which demographic variables confound this association. A third Cox regression model was performed with further covariate adjustment for comorbid conditions (history of myocardial infarction, stroke, congestive heart failure, cancer and diabetes), lifestyle factors (smoking, alcohol use and physical activity), dietary variables (calorie intake and percent calories from protein) and estimated glomerular filtration rate (eGFR). Finally, as higher phosphorus intake might be associated with better nutritional status, the effects of further adjusting for nutritional variables [serum albumin, body mass index (BMI) and LBM] were examined in a fourth Cox regression model.
The assumption of proportional hazards was examined by comparing the logarithm of the hazard ratio (HR) for each predictor variable in the first 3 years of follow-up to the logarithm of the HR of the predictor variables after Year 3. No models showed proportional hazards assumption violations with respect to dietary phosphorus intake.
The factors gender and stroke exhibited a significant deviation from proportional hazards (P < 0.05) in at least one of the models. Hence, rather than including these factors as covariates, each of the Cox regressions was stratified by each of these factors to allow separate baseline hazard functions within each stratum. In addition, quadratic terms were tested for each continuous covariate to test for the presence of nonlinear effects of that covariate. No quadratic terms were statistically significant.
Similar analyses were performed treating dietary phosphorus intake as a categorical variable with the lowest dietary phosphorus intake as the reference group.
Source...