Are Kidney Beans Good For Your Kidneys? A Close Look at the Link Between These Legumes and Kidney Health

2Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaFind articles by

2Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaFind articles by

2Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaFind articles by

2Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaFind articles by

Dietary factors play an important role in the development of chronic kidney disease (CKD). Nevertheless, there is still not a lot of strong evidence linking eating beans with CKD, especially in middle- and low-income groups. The point of this study was to look into how eating beans is related to signs of kidney damage and the number of adults in rural areas who have CKD.

A total of 20,733 rural adults from the Henan Rural Cohort Study in 2018–2022 were included. The total beans intake was collected using a validated food frequency questionnaire. The estimated glomerular filtration rate and the urinary albumin to creatinine ratio were used to find signs of kidney damage and CKD. We used generalized linear regression and logistic regression models to figure out how the amount of beans eaten relates to continuous and binary indicators of kidney function.

Of the 20,733 participants, 2,676 (12. 91%) subjects were identified as CKD patients. After taking into account possible confounders, people who ate more beans had a lower risk of CKD (odds ratio and 95% confidence interval, OR) (Q2: 200). 968(0. 866–1. 082); Q3: 0. 836(0. 744–0. 939); Q4: 0. 854(0. 751–0. 970)) and albuminuria (Q2: 0. 982(0. 875–1. 102); Q3: 0. 846(0. 750–0. 954); Q4: 0. 852 (0. 746–0. 973)), compared with the Q1. Each 5% increase in the daily intake of beans was significantly linked to a 5% and 4% decrease in the prevalence of albuminuria and CKD, respectively. These inverse relationships were also significant in the subgroups of men, elder, and high-income participants (p < 0. 05).

Eating more beans was linked to a lower risk of albuminuria and CKD in adults living in rural areas. This suggests that encouraging people to eat more soy foods could help lower the risk of CKD in adults living in rural areas.

CKD, a long-term disease where kidney structure and function stay abnormal, has become a major public health problem around the world in the last few decades, with a higher death rate and a heavier disease burden (1, 2). The GBD 2019 Diseases and Injuries Collaborators say that there were over 697 million people with CKD around the world in 2019 (3). According to the World Health Organization, CKD is very common and is rising quickly, especially in developing countries like China, which has the most CKD patients in the world, with about 1.2 million cases in 2019 (about 10% of the total population) (4). Many established risk factors for CKD have been studied in the past. These include high blood pressure, diabetes, dyslipidemia, metabolic syndrome, hyperuricemia, and lifestyle factors like socioeconomic status, physical activity, alcohol consumption, and more (5–8). However, there is mixed evidence about the link between different dietary factors and getting CKD, which means that the topic needs more research.

Soy is a popular food and a valuable source of nutrients, phytochemicals, and bioactive compounds (9). People in Asia, like China, Japan, and Korea, have eaten soy and its products for hundreds of years (10) The components of soy food have multiple health benefits. A lot of research has shown that eating soy or beans is linked to a lower risk of high blood pressure, diabetes, high uric acid, obesity, and CVD (10–12), all of which are closely linked to the development of CKD. However, the relationships between soy food consumption and renal function and CKD remain controversial due to limited evidence. Soy products are a good source of plant-based protein and other nutrients, so doctors recommend them to people with CKD (13) Still, a lot of people didn’t eat soy foods because they were afraid they would hurt their CKD (14) New evidence from studies on animals and people suggests that eating soy protein may delay the onset of kidney disease and CKD (15, 16). However, some studies did not observe a beneficial effect of bean intake on CKD. They found that soy protein intake did not significantly alter glomerular filtration rate or attenuate proteinuria (17, 18). Furthermore, one observational study showed that replacing animal protein with soy increased urinary protein excretion (19). A new population-based nutritional study also found that sticking to a healthy diet that includes soy products is linked to a lower risk of CKD getting worse (20). However, not many studies have looked at how eating soy or beans affects CKD or kidney function on their own, especially large-scale epidemiological surveys.

People in rural areas eat more beans and soybean products than people in cities, who tend to eat more animal-based foods (21). Moreover, the prevalence of CKD has been as high as 16. 40% in recent years (8). Since there were mixed results about how much beans can help with CKD, we looked at the links between total beans intake, kidney injury indicators, and CKD prevalence using the most recent data from the Henan Rural Cohort Study. Also, subgroup analyses were done to look into what changes the relationships between eating a lot of beans and a number of signs of kidney damage.

The people in the study came from the Henan Rural Cohort Study (Registration number: ChiCTR-OOC-15006699), which ran from July 2018 to September 2021. From 2018 to 2022, a total of 28,628 rural residents ages 18 to 79 filled out the questionnaires and underwent a physical exam as part of the follow-up study. Of these participants, 26,030 were interviewed at baseline and 2,598 were new to the cohort. The detailed study design, data collection, and measurements have been described elsewhere (22). In the current study, 21,079 participants completed the routine blood and urine measurements. Also, 211 participants were taken out because they had cancer (N = 200) or kidney failure (N = 11). Another 135 participants who were missing data on bean intake (N = 15), eGFR (N = 4), or ACR (N = 116) were also taken out. This left a final group of 20,733 participants for the current analysis. The flowchart of participant inclusion is shown in Supplementary Figure S1. The study protocols were approved by the Zhengzhou University Life Science Ethics Committee. All participants gave informed consent before the investigation.

Distributions and prevalence of kidney injury indicators by quartiles of total beans intake

shows a big difference in the types of kidney damage signs and how common they are based on the quartiles of total bean intake (all p 001). In Q2–Q4, the mean levels of eGFR were higher than those in the lowest quartile (Q1), but the mean levels of ACR were lower. Moreover, the prevalence of reduced eGFR, albuminuria and CKD tended to be lower in higher quartile groups. In particular, the prevalence of CKD in the Q1-Q4 groups was 14. 86, 13. 67, 11. 50, and 11. 43%, respectively ( ).

Dietary assessment and beans intake

The current study used a semi-quantitative 13-item food frequency questionnaire (FFQ) to collect dietary information. Individual data for the FFQ were obtained by experienced interviewers during a face-to-face visit. The 13-item FFQ had foods like fish, eggs, milk, fruits, vegetables, nuts, pickles, cereal, animal oil, and red and white meat. People were asked to say how often (never, day, week, month, year) and how much (kilograms, grams) they had eaten in the last 12 months. A validation study has demonstrated the reliability of the FFQ (23). Detailed information about the calculation of various types of food has been described in our previous study (23). Different types of food, like staples like rice, noodles, and steamed bread; red meat like pork, lamb, and beef; white meat like chicken and duck; fish like salmon, tuna, and trout; eggs like chicken, duck, and goose eggs; milk and dairy products like goat’s milk, yogurt, cheese, and other dairy products; fruits, vegetables, nuts, and peanuts; and grains like corn, sweet potatoes, and sorghum. In this study, “beans intake” meant the total amount of soybean, lentil, red bean, mung bean, black bean, pea, tofu, soy milk, dried tofu, vegetarian chicken, and other beans and bean products that people in the area usually eat. (21). In the main analyses, all participants were split into four groups based on the range of total beans they ate each day: Q1, beans intake 67 g/d; Q2, beans intake =6. 68–16. 67 g/d; Q3, beans intake =16. 68–50 g/d; and Q4, beans intake >50 g/d.

All of the people who took part were asked to come to the health examination center in their communities in the morning after fasting for at least eight hours the night before. Blood samples were taken from the antecubital vein by well-trained nurses and stored them under the right conditions. We sent serum samples to an OCHE Cobas C501 automatic biochemical analyzer to check for biochemical markers like fasting blood glucose, insulin, total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, uric acid, and creatinine. The eGFR was calculated using the 2009 CKD Epidemiology Collaboration equation (CKD-EPI creatinine equation) (23). Urine samples were also collected to detect routine urine substances such as urinary albumin and urine creatinine. The urinary albumin to creatinine ratio (ACR, mg/g) was calculated.

Albuminuria was defined as participants with an ACR > 30 mg/g. Indicators of kidney injury were the presence of a reduced eGFR (eGFR <60 ml/min/1. 73 m2) or albuminuria. If you have CKD, you either have albuminuria or your estimated glomerular filtration rate (eGFR) is less than 60 ml/min per 1. 73 m2 (8, 24).

For possible covariates, a validated questionnaire was used to get basic information like age, gender, level of education, average monthly income, smoking and drinking habits, and meat and food intake, as was already reported (21). Education level was classified into ≤primary, middle, and ≥ senior high school. Averaged monthly income was divided into three groups (<500 RMB, 500–1,000 RMB and ≥ 1,000 RMB groups). Smoking and drinking status were split into current or other groups. Current smokers were people who had smoked at least one cigarette a day for at least six months. Participants who consumed alcohol 12 or more times yearly without abstinence were considered current drinkers. Based on the International Physical Activity Questionnaire (IPAQ), levels of physical activity were grouped into light, moderate, and vigorous (25) Body mass index (BMI) was calculated according to the measurements of height and weight of participants. Based on the FFQ, daily intakes of red meat (g/day), white meat (g/day), fish (g/day), eggs (g/day), milk (g/day), vegetables (g/d), and fruits (g/d) were chosen as possible covariates that were linked to CKD (19). Also, a number of long-term diseases, including hypertension, T2DM, dyslipidemia, and hyperuricemia, were objectively evaluated and found to match previous definitions (26)

The basic information about the people who took part in the study is shown as the mean (standard deviation, SD) for continuous variables and the number (percentage) for categorical variables. We used Student’s t-test and Chi-square test for continuous variables and categorical variables, respectively, to compare basic characteristics based on the CKD condition (Yes or No). Participants were divided into quartiles of total beans intake (Q1-Q4). Then, the crude prevalence of reduced eGFR (eGFR <60 mL/min/1. 73 m2), albuminuria and CKD were calculated and compared according to quartiles of total beans intake.

In the main study, generalized linear regression models were used to look at how total bean intake related to eGFR and ACR (continuous outcomes) in the whole population. Effect estimates are presented as regression coefficients (β) and corresponding 95% confidence intervals (CIs). In addition, a multivariable-adjusted logistic regression model was used to find the odds ratios (ORs) and 95% confidence intervals (CIs) of the associations between the different levels of total bean intake and the rates of decreased eGFR, albuminuria, and CKD (the dichotomous outcomes). All regression models were analyzed using the lowest quartiles group as the reference group. We checked for p for linear trend across quartiles by using the median amount of beans eaten in each quartile as a linear variable in the regression models. The first model took into account the person’s age, gender, level of education, average monthly income, current smoking, current drinking, level of physical activity, and body mass index (BMI). The second model did the same thing but added in red-meat (g/day), white-meat (g/day), fish (g/day), eggs (g/day), milk (g/day), vegetables (g/d), and fruit (g/d).

We did sensitivity analyses to see how reliable our estimates were. First, we repeated the analyses to see how different quartiles of total bean intake affected lower eGFR, albuminuria, and the prevalence of CKD, while also taking into account T2DM, hypertension, dyslipidemia, and hyperuricemia based on model 2. Second, we split the whole population into men and women, found the soy quartiles for each gender, and used regression analyses to look at the effects of each gender. In addition, given that dietary pattern is more important than single food item intake. To see how strong the effect of eating a lot of beans on lower eGFR, albuminuria, and the prevalence of CKD is, we also looked at dietary patterns instead of just single foods in model 2. The four groups of eating habits were found using factor analysis with the standard principal component analysis method, which was based on earlier research (27, 28).

We did subgroup analyses to see how an increase of 50 grams of beans a day affected eGFR, albuminuria, and the number of people with CKD based on age, gender, and other factors. To do effect modification analysis, an interaction term between total beans eaten and the testing variable was added to the regression model. The interactions were considered present if a cross-product term was statistically significant.

All data were analyzed using SPSS software version 21. 0 and R software version 3. 5. 3. Two-tailed p values <0. 05 were considered statistically significant.

The demographic characteristics of the individuals according to their CKD status, are shown in . Among 20,733 participants, 2,676 (12. 91%) subjects with CKD. The mean age of the study population was 60. 19 years, and 12,908 (39. 6%) of the participants were women. People with CKD were older, less educated, made less money, and were less active than people without CKD. They also ate less red meat, fish, milk, fruit, and beans, and their eGFR was lower (all p < 0.05). 05); while they had higher BMI, higher ACR, hypertension, T2DM, dyslipidemia and hyperuricemia (all p < 0. 001). Also, Supplementary Table S1 in the additional materials shows similar distributions of demographic characteristics based on signs of kidney injury. There were 366 (1. 77%) participants with reduced eGFR (eGFR<60 mL/min/1. 73 m2) and 2,448 (11. 80%) participants with albuminuria.

Are Kidney Beans Beneficial for Kidneys? | Kidney Patient Diet 2020 | Kidney Expert (USA, UK, UAE)

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