Chronic Health Data
Is there a drug that can completely cure chronic diseases, excluding genetic and infectious ones?
Currently, no pharmaceutical drug or medical professional can completely cure chronic, non-genetic, non-infectious diseases. It is unlikely that such a cure will emerge in the future, as genetic adaptation takes many generations to metabolize new chemical compounds. Instead, the focus of treatment is on managing symptoms and controlling disease progression, often requiring long-term or lifelong medication.
So the answer is food or?
Empirical Evidence of Rising Chronic Disease
The increasing prevalence of chronic diseases in domesticated animals, including Homo sapiens, across different generations is supported by empirical evidence collected from extensive, systematic health surveys and studies. Data from sources such as the CDC's National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveillance System (BRFSS) show consistent trends of rising chronic disease rates over time.
This evidence points to a larger issue: evolutionary adaptation takes hundreds of thousands to millions of years to optimize metabolic function. No species—whether humans, pets, plants, or insects except some bacteria—can fully adapt to the synthetic chemical compounds introduced in just the last century. The rising burden of chronic conditions reflects our inability to quickly metabolize these new substances, underscoring the need for careful consideration of how modern innovations interact with our biology.
Chronic Diseases Are on the Rise based on data provided by the CDC
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80s: Over 90% of individuals experience chronic diseases.
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70s: Around 85% or more are affected.
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60s: Approximately 60% have at least one chronic condition.
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45-64: The rate of chronic diseases among people aged is notably increasing.
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Under 17 are seeing a rise in health issues compared to 50 years ago.
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"Chronic diseases, such as heart disease, stroke, cancer, chronic respiratory diseases, and diabetes, are leading causes of death globally. According to the World Health Organization (WHO), around 74% of deaths worldwide are due to chronic diseases. This amounts to approximately 41 million people dying from chronic non-communicable diseases (NCDs) each year."
Why Are Cures So Rare in Chronic Diseases?
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Chronic Diseases Are Complex: Chronic conditions often involve diet—which makes it challenging if they believe doctors and medicines can cure the root cause. Most treatments focus on managing or disguise the disease's progression, not curing it.
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Irreversible Damage: By the time chronic diseases are diagnosed by a blood test, the insulin level is too high, the body may have already undergone significant damage (e.g., nerve damage in diabetes or heart damage in heart disease), which can’t be undone with medication alone.
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Genetic Predisposition: The mainstream advocates that many chronic diseases are influenced by genetics, even though there were minimal chronic diseases 100 years ago, and non-domesticated species are not chronic diseases. This makes it difficult for the domesticated Homo sapiens to know that changing their diet could "cure" them.
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Autoimmune Nature: Diseases like type 1 diabetes, lupus, and rheumatoid arthritis are caused by the body's immune system attacking itself. While we can suppress this attack with drugs, completely resetting or reprogramming the immune system to stop the attack permanently is difficult because they don't know a diet can reverse that.
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Degenerative Nature: Many chronic diseases, like Alzheimer's or Parkinson's, are neurodegenerative, meaning they progressively worsen over time as cells die or become damaged because of their mothers' and their early age's diet. Once the damage has occurred, current medicine cannot reverse it.
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Why Don't Doctors Test Insulin Levels First? One significant issue in the management of chronic diseases like diabetes is that doctors often do not test insulin levels before assessing blood sugar levels. This oversight can lead to late diagnoses, as patients may only be informed of high blood sugar levels after they have already progressed to stages of insulin resistance or pancreatic dysfunction.Insulin Resistance and Late Diagnosis
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By the time a patient receives a diagnosis based on elevated blood sugar, they may have already passed through critical stages of insulin resistance. Insulin resistance occurs when the body's cells become less responsive to insulin, prompting the pancreas to produce more of the hormone. This compensatory mechanism can mask underlying issues until significant damage has occurred.
A Our Prediction
If we continue on this trajectory—if we don’t change the way we think about food and health—almost all newborns today will likely face chronic diseases by the time they reach mid-age. This is not just a prediction; it’s an inevitable outcome based on the current trends and the widespread acceptance of harmful ingredients in our food supply.
Is CDC Data Trustworthy?
The data provided by the CDC through their various surveys and reports is generally considered statistically reliable and valid for several reasons:
1 Large Sample Sizes:
The CDC uses large sample sizes in their surveys and studies, which helps ensure that the data is representative of the broader population. Larger samples provide more reliable estimates and reduce the margin of error.
2 Rigorous Methodology:
The CDC employs rigorous statistical methods and quality control measures in data collection and analysis. This includes random sampling, stratified sampling, and sophisticated statistical techniques to ensure accuracy and reliability.
3 Transparency and Documentation:
The CDC provides detailed documentation on their methodologies, including sampling techniques, data collection procedures, and statistical analyses. This transparency allows others to review and validate the methods used.
4 Regular Updates
The CDC regularly updates their data and reports to reflect the most current information. Ongoing data collection and periodic updates help track trends and ensure the data remains relevant.
5 Peer Review and Validation
Many of the CDC's reports and findings undergo peer review and validation by other researchers and public health experts. This helps ensure that the data is accurate and the conclusions are sound.
6 Comprehensive Data Collection
The CDC collects data from multiple sources, including national surveys, health records, and vital statistics. This comprehensive approach helps to cross-validate findings and provides a more complete picture.
7 Adherence to Standards
The CDC adheres to established standards and best practices in public health research and statistics. This adherence helps maintain the quality and reliability of the data.
Considerations When Interpreting Data:
1 Context and Limitations:
While the data is statistically reliable, it’s important to consider the context and limitations. For example, observational data can identify correlations but may not establish causation. Interpreting data within the context of study design and limitations is crucial.
2 Data Quality and Completeness:
Data quality can vary, and there may be missing or incomplete data in some studies. Understanding how data quality issues are addressed is important for interpreting results.
3 Updates and Changes:
Public health data can evolve over time, and updates or changes in data collection methods can impact trends. Staying informed about recent updates and methodological changes is essential.
In summary, the CDC’s data is generally trusted for its statistical rigor and reliability. However, as with any data, it's important to consider the methods used, potential limitations, and the context in which the data is presented. For a more detailed evaluation, reviewing the specific methodologies and documentation provided by the CDC for each dataset or report is advisable.
Types of Data Collected by the CDC:
National Health and Nutrition Examination Survey (NHANES)
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Sample Size for Children: NHANES typically includes thousands of children and adolescents each year. The sample size for the pediatric population is around 1,000 to 1,500 children annually, depending on the specific age range and focus.
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Purpose: Provides data on the health and nutritional status of children and adolescents through health examinations, interviews, and laboratory tests.
Youth Risk Behavior Surveillance System (YRBSS)
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Sample Size: Includes data from surveys of high school students (grades 9-12) with sample sizes typically ranging from 10,000 to 20,000 students per year.
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Purpose: Monitors health behaviors and experiences among adolescents, including behaviors that can contribute to chronic diseases.
National Vital Statistics System (NVSS)
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Sample Size: Includes data from surveys of high school students (grades 9-12) with sample sizes typically ranging from 10,000 to 20,000 students per year.
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Purpose: Monitors health behaviors and experiences among adolescents, including behaviors that can contribute to chronic diseases.
Children's Behavioral Health Data (Various State-Based Surveys)
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Sample Size: Varies by state and survey, but generally includes a representative sample of children within the state.
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Purpose: Collects data on behavioral health, including conditions such as ADHD, autism spectrum disorders, and other mental health issues.
Sources of Data for Individuals Under 17:
Behavioral Risk Factor Surveillance System (BRFSS)
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Sample Size: Approximately 400,000 to 500,000 adults annually.
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Purpose: Collects data on health-related behaviors, chronic conditions, and preventive services among U.S. adults.
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Method: State-based telephone surveys with a mix of landline and mobile phone interviews.
National Health and Nutrition Examination Survey (NHANES)
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Sample Size: Approximately 5,000 to 10,000 people per year.
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Purpose: Provides data on the health and nutritional status of adults and children in the U.S. through interviews, physical examinations, and laboratory tests.
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Method: In-person interviews and health examinations at mobile examination centers.
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General Notes on Sample Size
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Large Samples: These surveys generally have large sample sizes to ensure that the data is representative of the broader population and allows for detailed analysis across various subgroups.
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Specific Surveys: Sample sizes can vary based on the focus of the survey, the population being studied, and the available resources.
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For precise sample sizes and methodologies, you can check the specific methodology sections of CDC reports or data collections, which are usually detailed in their publications and data briefs.