Detailed Description:
Experimental design: Seventy-six adults aged 18-50 years (19 white, 19 Black, 19 Hispanic, and 19 Asians) will be recruited to complete 16 in each group and tested on two levels of dietary salt (lower = 2300 mg/Na/d and higher = 3700 mg Na/d) in randomized order. The primary outcome measures are fractional calcium absorption and urinary calcium excretion. Secondary outcome measures are urinary sodium excretion and whole blood serum ionized calcium and magnesium concentrations.
Participants will be recruited by poster or by passed out flyers on and near campus, through presentations to organizations where potential participants attend (YMCA, fraternities, churches, etc.), and advertising through newspaper ads, social media, and others. Respondents will be invited for a screening visit at the Exercise and Nutritional Sciences Department to determine eligibility and to sign a consent form.
Eligible participants will have 3 of 4 grandparents self-identified as the racial/ethnic group. They will not have taken any vasoactive or calcium metabolism-altering medications (statins, antihypertensives, aspirin, steroids, bisphosphonates, thiazide diuretics, hormone replacement therapy, and antidepressants), experienced a bone fracture within the past 6 months, had diabetes, cancer, liver disease, gastrointestinal disease (e.g.: Crohn's disease, irritable bowel syndrome, malabsorption syndrome), decreased kidney function, or have smoked cigarettes within the past 12 months before the study. Eligible subjects will also not have had habitually consumed \> 1000 mg Ca/d from food or supplements.
Upon providing written consent, applicants will complete a brief questionnaire on medical history, physical activity, and supplement use and a 4-day diet record to assess usual dairy intake as well as nutrients known to influence calcium and sodium metabolism i.e. calcium, sodium, magnesium, protein, fiber. Waist circumference, height, and weight will be measured to determine the body mass index (BMI) and a fasting blood sample will be collected to assess blood biochemistries and metabolomics. A DXA will be performed to determine total body calcium as a covariate.
Enrolled subjects will be randomized to a sequence of 2 treatments of a high (3700 mg sodium) or low (2300 mg sodium) diet for 2-days each separated by a 4-week washout period during which they will consume self-selected diets. All food and beverages will be provided to control for the nutrients known to influence calcium metabolism with salt being the main difference between the periods. Menus will be devised to control for energy, calcium, sodium, macronutrients, and fiber. Portions will be adjusted for energy needs of the participant. They will be asked to discontinue taking any dietary supplements 30 days prior to the study and to abstain from caffeine, alcohol, and strenuous exercise for 24 hours before each test session. Participants will be asked to collect urine for 48 hours to measure sodium, calcium, and magnesium excretion and a stool sample for measuring fecal metabolomics. On the following day. Participants will be asked to abstain from all foods and beverages not provided until the last blood draw. Blood pressure will be measured on the last day of each treatment.
Analytical methods:
Total calcium, sodium, and magnesium, milk, and urine samples will be analyzed chemically. Isotope ratios in urine and plasma will be measured by ICP mass spectrometry (Element2/XR, Thermo Fisher Scientific). Fractional calcium absorption will be calculated according to the following formula:
Fractional Ca absorption (%)=(Serum 〖enrichment with 44〗\_Ca)/〖Serum enrichment with 43〗\_(Ca ) ×(Dose 43\_Ca)/(Dose 44\_Ca )×100.
To control for factors that might affect calcium absorption, serum vitamin D and parathyroid hormone will also be measured by liquid chromatography-mass spectrometry and commercially available ELISA kit, respectively.
Whole blood ionized calcium and magnesium will be analyzed by a Nova 8 Electrolyte Analyzer. We demonstrated that this method was more sensitive than serum or urinary total magnesium to recent dietary magnesium, and thus, has been proposed as a magnesium status biomarker.
Plasma and fecal metabolomics will be performed by mass spectrometry.
Statistical analysis:
The primary outcome measure is fractional calcium absorption, expressed as percent of the ingested tracer. Two factor analysis (salt level and race/ethnicity) will be analyzed using a mixed linear model that takes into account the cross-over characteristic of the design with two treatments administered in random order for each subject. The major questions of interest, i.e. comparison of calcium absorption and excretion across race/ethnicity and response to dietary salt, will be examined as contrasts within this statistical model. Investigators will attempt to equalize the number of men and women in each group to explore sex differences though there is no a priori reason to assume there will be sex differences. Racial/ethnic differences in calcium absorption in response to dietary sodium have not been reported. Thus, urinary calcium excretion from previous studies will be used to perform power calculations to determine sample size. Black-White differences in urinary calcium excretion in response to dietary sodium using a cross over design have been reported in adolescents. Means and SD of urinary calcium (mg/d) in adolescent girls were 107±15 on a high sodium diet and 69±12 on a low sodium diet for White girls compared to 53 ± 10 and 50±9 on high and low sodium diets, respectively, for Black girls. This difference in response to sodium gives 90% power with a sample size of 6 for either a racial difference on a high salt diet or a sodium effect in a crossover design. The response of Asians or Hispanics to salt on calcium metabolism is not known, but differences are expected to be more subtle than between Black and White groups. The smaller racial difference between Black and White participants on a low sodium diet requires 16 subjects per group for 80 % power. Thus, 16 completers per group are proposed. Correlations and linear regression methods will be used to explore the relationships between outcome variables for specific treatments and subject characteristics. All statistical analyses will be performed using SAS (version 9.3, SAS Institute).