Participants
This cross-sectional study was conducted on 178 elderly subjects (51 men and 127 women) with a mean age of 67.04 (60-83), referred to health centers in Tehran. Participants were selected using two-stage cluster sampling of 25 Health centers in Tehran. Health centers in Tehran were divided into five regions: North, South, East, West and Central and then prepared a list of health centers in each area and 25 health centers were selected randomly (in attention to constraints budget and time) based on the number of health centers in each region proration. Then the total number of samples (178) divided by the number of health centers (25) and obtained the number of samples in each home centers.
This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the ethics committee of Tehran University of Medical Sciences (Ethics Number: IR.TUMS.VCR.REC.1396.2307). Written informed consent was obtained from all subjects/patients.
Anthropometric measurements
Patient’s height was measured without shoes by a wall stadiometer with sensitivity of 0.1 cm (Seca, Germany) and weight by digital scale (Seca 808, Germany) with an accuracy of 0.1 kg with light clothes (without a coat and rain coat). BMI was calculated by dividing weight in kilograms by the square of height in meters. Waist circumference was measured with a tape measure between the iliac crest and the lowest rib on the exhale. Body fat (%) was measured using body composition analyzer (InBody 720, Biospace, Tokyo, Japan).
Assessment of other variables
We obtained information on age, sex, physical activity, smoking, marital status, diabetes, hypertension and dyslipidemia through questionnaires. Physical activity categorized into very low, low and moderate/high. Smoking classified as non-smoker and former/current smoker. Diabetes, hypertension and dyslipidemia quantified as yes or no.
Laboratory investigation
10 ml of blood and 3 ml urine samples were obtained between the hours of 7-10 am from all of fasted participants. Then blood sample were collected in acid-washed test tubes without anticoagulant. After storing at room temperature for 30 minutes and clot formation, blood samples were centrifuged at 1500 g for 20 minutes. Serums were stored in - 80° C until future testing. Serum Human N-MID Osteocalcin was measured by ELISA kit (Bioassay Technology Laboratory, Shanghai Crystal Day Biotech Co., Ltd., Shanghai, China), with CV<10% and sensitivity of 0.22 ng/ml. The Human C-telopeptide of type Ⅰ collagen (u-CTX-I) ELISA kit (Bioassay Technology Laboratory, Shanghai Crystal Day Biotech Co., Ltd., Shanghai, China), with intra-Assay: CV<10% and sensitivity of 0.24 ng/ml was used for the quantitative measurement of CTX-I in urine. The measurement of highly sensitive C-reactive protein (hs-CRP) was performed by immunoturbidimetric assay based on the kit instructions (Pars Azmoon, Iran, and Tehran). The 25(OH) D and PTH were assessed by means of an enzymatic method, using commercial kits (with Pars Azmoon, Iran, Tehran and DRG, Marburg, Germany,) respectively. Insulin resistance and insulin sensitivity were assessed using the HOMA-IR [19] and the QUICKI [20], respectively.
Dietary assessment
Dietary intakes of subjects was evaluated by means of a valid and reliable semi-quantitative food frequency questionnaire (FFQ), with 168 food items [21]. Trained researchers via face-to-face interviews, asked subjects to report their frequency of intake of each food item, during the past year on a daily, weekly, or monthly basis. These reports were converted to daily intakes, then we used this dietary data to generate three versions of a plant-based diet: an overall PDI, hPDI, and uPDI [22]. Supplementary table 1 details examples of food group constituents. We created 18 food groups based on nutrient and culinary similarities within the larger categories of healthy plant foods (whole grains, fruits, vegetables, nuts, legumes, vegetable oils, tea/coffee), less healthy plant foods (fruit juices, refined grains, potatoes, sugar-sweetened beverages, sweets/desserts), and animal foods (animal fat, dairy, eggs, fish/seafood, meat, miscellaneous animal-based foods). The classification of mixed composition foods was according to predominate ingredient. Participants were ranked into quintiles according to their food intakes, which were subsequently given positive or inverse scores. With positive scores, participants above the highest quintile of a food group received a score of 5 and those below the lowest quintile received a score of 1. With inverse scores, this pattern of scoring was inversed. For PDI, plant food groups were given positive scores, while animal food groups were given inverse scores. For hPDI, positive scores were allocated to healthy plant food groups, and inverse scores to less healthy plant food groups and animal food groups. Finally, for uPDI, positive scores were allocated to less healthy plant food groups, and inverse scores to healthy plant food groups and animal food groups. The 18 food group scores were summed to establish the indices.
Statistical analysis
All statistical analysis was performed with the SPSS (Statistical Package for Social Sciences) for Windows 25.0 software package (SPSS, Chicago, IL). The level of statistical significance was pre-set at p< 0.05. The normality of data was evaluated by the Kolmogorov and Smirnov test. People were grouped based on the tertiles of PDI, hPDI and uPDI. To compare general characteristics among tertiles, we used one-way ANOVA for quantitative variables also qualitative variables were evaluate by Chi-square tests. Pearson correlation was conducted to assess the relation of food groups intake with test variables including serum osteocalcin, urine CTX-I, hs-CRP, 25(OH) D, PTH, serum insulin, HOMA-IR, and QUICKI. Multivariate adjusted means were performed to evaluate the relationship between tertiles of PDI, uPDI and hPDI with other variables including osteocalcin, urine CTX-I, hs-CRP, 25(OH) D, PTH, serum insulin, HOMA-IR, and QUICKI (adjusted for age, sex, BMI, smoking, physical activity, marital status, disease and energy intake). Multiple linear regression analysis was used to evaluate the association between serum osteocalcin, urine CTX-I, hs-CRP, 25(OH) D, PTH, serum insulin, HOMA-IR, and QUICKI with PDI, uPDI and hPDI score after adjustment for covariates, including age, sex, BMI, smoking, physical activity, marital status, disease and energy intake. In all the above-mentioned analyses, first tertile was regarded as the reference category.