Can too much protein affect your prostate?

Background. Growing evidence demonstrated that dietary protein intake may be a risk factor for prostate cancer and elevate the level of prostate-specific antigen (PSA).

lipidworld.biomedcentral.com - Is there a non-linear relationship between dietary protein intake and ...

Is turmeric good for diabetes?

Turmeric and its ingredient curcumin may assist in controlling diabetes. Studies have shown that it can reduce blood sugar levels, increase insulin...

Last updated Jul 30, 2018

What fruit spikes your blood sugar?

Some commonly eaten fresh fruits may raise your blood sugar more quickly than others. These include figs, grapes, mangos, cherries and bananas. Eat...

Last updated Apr 25, 2018

Promotion

Data source

Since 1960, the National Centers for Disease Control and Prevention (CDC) National Center for Health Statistics has conducted a National Health and Nutrition Examination Survey (NHANES) every two years to provide national estimates of the health and nutritional status of non-institutional populations in the United States. Data from the official website of NHANES (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx) is available for free download. The NHANES protocol was reviewed and approved by the National Center for Health Statistics research ethics review board. All participants received written informed consent. More detailed information about NHANES can be found on the official website.

Study population

The NHANES database only has PSA data for 2003–2010, therefore we integrated data from four two-year NHANES survey cycles: 2003–2004, 2005–2006, 2007–2008 and 2009–2010, and performed secondary data analysis. We restricted the population included in the analysis to men 40 years of age and older and did not have a history of prostate tumor [16]. They provided blood samples for PSA assessment as part of NHANES. The participants were screened according to the following exclusion criteria: (1) Men with prostate cancer, prostatitis, or recent prostate surgery (ie, a rectal exam within 1 week, and a prostate biopsy within 1 month, surgery or cystoscopy) were not included in the study. (2) We also excluded men who used 5ARI or other forms of hormone therapy (ie, testosterone replacement or medical castration) and drugs, with incomplete clinical or socio-demographic data. After a series of screening, 6403 out of 42,470 participants were included in the study. The detailed flowchart is shown in Fig. 1. Fig. 1 Flow chart of procedures from identification of eligible patients to final inclusion Full size image

Variables

In the current study, the targeted independent variable was dietary protein intake (gm). The US Department of Agriculture (USDA) Automatic Multiple Pass Method (AMPM) was used to collect dietary intake data by interviewers 24 h a day. A detailed description of the dietary interview method has been described elsewhere [17]. The targeted dependent variable was PSA (ng/mL). For the present study, serum PSA concentration (ng/mL) was measured using the Beckman Access Immunoassay System with the Hybritech Total PSA Assay (Beckman Coulter, Fullerton, CA) [18]. Covariates were selected based on previous studies demonstrating the link between these covariates and dietary protein intake and/or prostate cancer/PSA [16, 19]. Covariates included demographic, dietary, biological, and immunological variables. Variables included in the database file were as follows: continuous variables included LDL-cholesterol (mg/dL), Poverty income ratio (PIR), Body mass index (Kg/m2), Total alcohol intake on the first day (gm), Vitamin D (ng/mL), C-reactive protein(mg/dL), Glycohemoglobin (%), HDL-cholesterol (mg/dL), cigarettes per day during past month, Age (year), Total protein intake on the first day (gm) and Triglycerides (mg/dL). Categorical variables consisted of race, hypertension history, diabetes history, coronary heart disease, stroke, education level, marital status, physical activity, and enlarged prostate. In general, covariates relate to demographic data, dietary data, physical examination data, and comorbidities in the NHANES database. A more detailed explanation of the variables can be found on the NHANES official website.

Does zinc make you last longer in bed?

A 2016 study also found that a supplement containing folic acid, zinc, and the herb golden root improved the ejaculatory control of those affected...

Last updated May 13, 2022

What is a healthy male boyfriend?

For a man, 2–5% fat is essential, 2–24% fat is considered healthy, and more than 25% classifies as obesity. For a woman, 10–13% fat is essential,...

Last updated Dec 20, 2020

Promotion

Statistical analysis and missing data

We conducted a statistical analysis according to the criteria of the CDC guidelines (https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx). In order to enhance the statistical strength, we transformed the dietary protein intake by per 10 g change as the targeted independent variable, and we use log2 transformation and use the transformed data as the independent variable for data analysis because PSA is skewed distribution. Continuous variables were expressed as mean ± standard deviation (normal distribution) or median (quartile) (skewed distribution), and categorical variables were expressed in frequency or as a percentage. To investigate whether dietary protein intake is related to PSA levels in selected participants, our statistical analysis consists of three main steps. Firstly, the dietary protein intake was divided into four groups according to the quartile levels and presented the distribution of baseline data of patients included in this study in different dietary protein intake groups (Quartile). The chi-square tests (categorical variables), One –Way ANOVA (normal distribution), or Kruskal-Wallis test (skewed distribution) was used to demonstrate for differences among four quartile groups. In the second step of data analysis, the weighted univariate and multivariate linear regression model was employed. Four statistical models were constructed: model I, no covariates were adjusted; model II, only adjusted for socio-demographic data; model III, model 2 + other covariates exhibited in Table 1, model IV, a weighted generalized additive model (GAM). The third step of data analysis was to conduct the GAM model and smooth curve fitting (penalized spline method) to explore the nonlinearity association between dietary protein intake and PSA levels. If the GBM model detects nonlinearity, we first calculate the inflection point using a recursive algorithm and then construct a weighted two-stage linear regression model on both sides of the inflection point. We determined the best fit model based on the P-value of the log-likelihood ratio test (linear regression model and two piecewise linear regression models).

Table 1 Baseline characteristics of selected participants Full size table

How do you fix low testosterone?

The best way to improve testosterone levels is by adopting some lifestyle habits that can improve overall health and well-being. Getting enough...

Last updated Aug 31, 2021

Which seeds can regrow hair?

Here is a list of common seeds that promote healthy hair growth Sesame seeds. Good hair growth requires the right nourishment. ... Kalonji seeds....

Last updated Mar 23, 2020

Promotion

Missing data addressing is needed for the accuracy of data analysis because a series of variables in the NHANES database have different degrees of missing. If only using complete case for data analysis, it will cause a large number of samples to be lost and may produce bias in our findings. Therefore, we have adopted multiple interpolations, the main purpose of which is to maximize statistical power and minimize bias that might occur covariates with missing data were excluded from data analyses. We created 5 imputed datasets with chained equations using a mice software package. In addition, we used sensitivity analysis to identify whether created complete data had a significant difference from pre-imputation data. Our findings demonstrated that created complete data showed no significant difference from raw data. Therefore, all results of our multivariable analyses were based on the imputed datasets and were combined with Rubin’s rules. To ensure the robustness of data analysis, we did the following sensitivity analysis: (1) we converted the dietary protein intake into a categorical variable by quartile and calculated the P for trend. The purpose was to verify the results of dietary protein intake as a continuous variable and to observe the possibility of nonlinearity; (2) we employed the weighted GAM model to adjust the continuous variables in model III. All analysis was performed using statistical software R (http://www.r-project.org, The R Foundation) and EmpowerStats (http://www.empower-stats.com, X&Y Solutions, Inc., Boston, MA). A p-value of less than 0.05 (two-sided) was considered statistically significant.

lipidworld.biomedcentral.com - Is there a non-linear relationship between dietary protein intake and ...

Can a man perform without a prostate?

Additionally, because the prostate gland and seminal vesicles make the majority of semen fluid, men after prostatectomy will no longer ejaculate....

Last updated Apr 18, 2021

What slows prostate cancer?

Eat more fruits and vegetables. The antioxidant lycopene, which is plentiful in cooked or processed tomatoes, has been shown in some studies to...

Last updated Oct 8, 2018

Promotion

What is the ideal height for long life?

In this study, men who were 5'2″ or shorter were more likely to have a protective form of the FOX03 gene, and lived the longest. Those over 5'4″...

Last updated Feb 17, 2021

Promotion

Can a CT scan detect cancer?

A CT scan (also known as a computed tomography scan, CAT scan, and spiral or helical CT) can help doctors find cancer and show things like a...

Last updated Apr 8, 2020