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Weight

Body weight management (weight loss focus); key observations, notes, tips and tricks


      • The scientific evidence does seem to favour a largely wholefood (and if safe, unprocessed / minimally processed with ideally a reasonable proportion consumed raw or if cooked, minimally cooked) plant based diet (vegetables, legumes, grains, seeds, nuts, herbs, spices, fruit) with as much plant based wholefood variety that you can manage (the consumption of about 30 different types of plants per week being suggested as a reasonable target). The inclusion of some live fermented foods may also be beneficial.

          • Number of deaths and DALYs and age-standardised mortality rate and DALY rate (per 100 000 population) attributable to individual dietary risks at the global and SDI level in 2017. DALY=disability-adjusted life-year. SDI=Socio-demographic Index.

        • Dietary risk factor exposure definitions, optimal level, and data representativeness index, 1990–2017
          Exposure definitionOptimal level of intake (optimal range of intake)Data representativeness index (%)
          Diet low in fruitsMean daily consumption of fruits (fresh, frozen, cooked, canned, or dried fruits, excluding fruit juices and salted or pickled fruits)250 g (200–300) per day94·9
          Diet low in vegetablesMean daily consumption of vegetables (fresh, frozen, cooked, canned, or dried vegetables, excluding legumes and salted or pickled vegetables, juices, nuts, seeds, and starchy vegetables such as potatoes or corn)360 g (290–430) per day94·9
          Diet low in legumesMean daily consumption of legumes (fresh, frozen, cooked, canned, or dried legumes)60 g (50–70) per day94·9
          Diet low in whole grainsMean daily consumption of whole grains (bran, germ, and endosperm in their natural proportion) from breakfast cereals, bread, rice, pasta, biscuits, muffins, tortillas, pancakes, and other sources125 g (100–150) per day94·9
          Diet low in nuts and seedsMean daily consumption of nut and seed foods21 g (16–25) per day94·9
          Diet low in milkMean daily consumption of milk including non-fat, low-fat, and full-fat milk, excluding soy milk and other plant derivatives435 g (350–520) per day94·9
          Diet high in red meatMean daily consumption of red meat (beef, pork, lamb, and goat, but excluding poultry, fish, eggs, and all processed meats)23 g (18–27) per day94·9
          Diet high in processed meatMean daily consumption of meat preserved by smoking, curing, salting, or addition of chemical preservatives2 g (0–4) per day36·9
          Diet high in sugar-sweetened beveragesMean daily consumption of beverages with ≥50 kcal per 226·8 serving, including carbonated beverages, sodas, energy drinks, fruit drinks, but excluding 100% fruit and vegetable juices3 g (0–5) per day36·9
          Diet low in fibreMean daily intake of fibre from all sources including fruits, vegetables, grains, legumes, and pulses24 g (19–28) per day94·9
          Diet low in calciumMean daily intake of calcium from all sources, including milk, yogurt, and cheese1·25 g (1·00–1·50) per day94·9
          Diet low in seafood omega-3 fatty acidsMean daily intake of eicosapentaenoic acid and docosahexaenoic acid250 mg (200–300) per day94·9
          Diet low in polyunsaturated fatty acidsMean daily intake of omega-6 fatty acids from all sources, mainly liquid vegetable oils, including soybean oil, corn oil, and safflower oil11% (9–13) of total daily energy94·9
          Diet high in trans fatty acidsMean daily intake of trans fat from all sources, mainly partially hydrogenated vegetable oils and ruminant products0·5% (0·0–1·0) of total daily energy36·9
          Diet high in sodium24 h urinary sodium measured in g per day3 g (1–5) per day*26·2
          To reflect the uncertainty in existing evidence on optimal level of intake for sodium, 1–5 g per day was considered as the uncertainty range for the optimal level of sodium where less than 2·3 g per day is the intake level of sodium associated with the lowest level of blood pressure in randomised controlled trials and 4–5 g per day is the level of sodium intake associated with the lowest risk of cardiovascular disease in observational studies.
        • For research that estimates the impact of food choices on life expectancy see the following link:
          • https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003889
            • For the online calculator created as part of the above modelling research that enables the instant estimation of the effect on life expectancy by making a range of dietary changes see the following link:
            • Expected increase in life expectancy for optimising different food groups with diet changes initiating from various ages between 20 and 80 years of age and a less optimal but potentially more feasible to adopt diet see the following chart from the above modelling research: 
                • For the optimal diet and feasibility approach diet, the following intakes were used: 225 g and 137.5 g whole grains (fresh weight), 400 g and 325 g vegetables, 400 g and/ 300 g fruits, 25 g and 12.5 g nuts, 200 g and/ 100 g legumes, 200 g and 100 g fish, 25 g and 37.5 g eggs, 200 g and 250 g milk/dairy, 50 g and 100 g refined grains, 0 g and 50 g red meat, 0 g and 25 g processed meat, 50 g and 62.5 g white meat, 0 g and 250 g sugar-sweetened beverages, and 25 g and 25 g added plant oils. Note that lines for life expectancy for red and processed meat changes are overlapping and similarly also for white meat and added oils.





        • For information about the optimal amount of sleep see the following chart:

    • Finding the diet approach(es) that best works for you as an individual (by trial and error) and sticking to it/them is key.
    • It can be difficult to manage and be accurate with calorie intake to ensure a deficit without actually planning and recording it.
    • For many people following a calorie deficit diet increases appetite.
    • Weighing yourself frequently (at least several times per week or even daily at the same time of the day and under similar conditions) and recording it is generally seen as a useful aid to effectively managing weight and can provide an opportunity to learn more about how food and activity affect your weight.
    • Setting a weight loss goal can be useful as can weekly weight loss targets.
      • For online calculators that can be used to estimate changes in body weight as a result of changes in your daily calorie balance see the following links:
      • See the following link to research that suggests some weight loss calculators may overestimate the energy requirements for more obesity susceptible individuals:
        • https://www.mdpi.com/2072-6643/9/9/1012/htm
          • Obesity susceptible individuals self identified themselves in this study by answering the following statements positively; 1. I am a person who needs to eat small amounts of food to manage my weight and 2. I am a person who gains weight easily and the following statements negatively; 1. I am a person who can eat whatever I like without gaining weight 2. I am a person who loses weight easily 3. I am a person who maintains my weight easily 4. I am a person who finds it difficult to put on weight.
    • If combined with strength/resistance exercise to maintain / build muscle mass or for very large daily calorie deficits sufficient protein is required (and probably vitamin and mineral supplementation in the latter case too).

                  • For a video that is reasonably consistent with the above with a practical focus (which displays preserved human body parts) see the following link:





    Foods / drink that may aid weight loss




    • The substances listed below can have body weight reduction impacts (the research indicates between a 1 to 2.5% body weight reduction after at least 3 months of use, depending on the food) so relatively small in the scheme of things but on the basis of every little can help and taking a marginal gains approach they may be worth trying. This assumes you can tolerate them although in general they seem to be well tolerated by most individuals. Their effectiveness may vary by individual too. They all also appear to have potential general health benefits as well. I have listed them in order of what I have determined to be the greatest to least impact on body weight reduction although the significant variances in study approaches makes this difficult to do and so it is my best guess following a review and comparison of all the studies. A number of the studies were undertaken with participants on a calorie restricted diet and showed additional weight loss compared to the control participants. If each of the foods worked additively (and I haven't come across any research about this to say this would or wouldn't be the case) and consumed them all whilst following a calorie restrictive diet you you may potentially achieve up to about a 15% extra body weight reduction but that conclusion is speculative (alternatively you could just eat less and include one or more of them in your diet for the potential health benefits).











      • Daily consumption of fermented Kimchi compared to the consumption of fresh Kimchi was found to have a significant reduction on waist to hip ratio and percent body fat. See the research abstract by following the link below.



    Commercial Weight Loss Supplements
    • The use of commercial weight loss supplements is probably not such a good idea unless you have researched the ingredients, you understand your individual tolerance to them and you are sure what they say they contain they actually contain. For a good video on the subject see the following link:



    Weight Loss Diets

    • For a clear and concise small publication that addresses crash dieting and dieting in general and considers different approaches including detailing a crash dieting approach see the following information:
      • The Rapid Fatloss Handbook A Scientific Approach to Crash Dieting
        • Author: Lyle McDonald
        • Publisher: bodyrecomposition.com
        • In a nutshell the above book advises not to crash diet and explains the reasons for not doing so and actually promotes a nutritionally balanced moderate long term dieting approach. It does provide a scientific approach to crash dieting for those that insist on doing so but clearly advises against it. See the following link to a short article that defends moderation as a better approach:

    • Research suggests that no one diet is significantly better than another overall and that the key challenge is to be able to manage weight control over the longer term. This is probably best done by incorporating diet change to be part of your ongoing lifestyle with individual circumstances and preferences taken into account. If sticking to a more rigid diet makes this harder to do long term this is probably not going to be a good choice. See the following link to the research:





    Weight Loss Medications



    Association between BMI and all-cause mortality modification by diet quality (from a population-based cohort study of 80 thousand adults in Sweden published in 2020)


    • Association between BMI (A for all-cause mortality and B for cardiovascular mortality) and an mMED score (C for all-cause mortality and D for cardiovascular mortality) with mortality. The dark gray shaded regions in the figures correspond to 95% CIs, and the spike plots represent the distribution of BMI and mMED scores, respectively. Assessed by multivariable-adjusted HRs using of Cox regression analysis and restricted cubic splines, with a BMI of 25 kg/m2 and mMED score of 8 units as references. HRs adjusted for sex, age (splines with 2 knots), educational level (≤9, 10–12, >12 years, other), living alone (yes or no), leisure time physical exercise during the past year (<1 1="" 2="" 4="" h="" w="">5 h/w), walking/cycling (almost never, <20 1="" 20="" 40="" d="" h="" min="">1.5 h/d), height (splines with 2 knots), energy intake (splines with 2 knots), smoking habits (current, former, never), Charlson’s weighted comorbidity index (continuous; 1–16), and diabetes mellitus (yes/no). BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; mMED, modified Mediterranean-like diet.
                The higher the mMED score the greater the compliance to the modified Mediterranean-like (mMED) diet.



    • Associations of combinations of BMI and adherence to an mMED with all-cause (A) and CVD mortality (B). Estimated by multivariable-adjusted HRs by use of Cox regression analysis with a normal BMI and high adherence to mMED as the reference. The CI in each subpanel is expressed both in numbers and as a line representing the width. HRs adjusted for sex, age (splines with 2 knots), educational level (≤9, 10–12, >12 years, other), living alone (yes or no), leisure time physical exercise during the past year (<1 1="" 2="" 4="" h="" w="">5 h/w), walking/cycling (almost never, <20 1="" 20="" 40="" d="" h="" min="">1.5 h/d), height (splines with 2 knots), energy intake (splines with 2 knots), smoking habits (current, former, never), Charlson’s weighted comorbidity index (continuous; 1–16), and diabetes mellitus (yes/no). BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; mMED, modified Mediterranean-like diet.
              The higher the mMED score the greater the compliance to the modified Mediterranean-like (mMED) diet.





    Alcohol

      • For risk comparison in 2018, 45 in 100,000 people were killed or seriously injured in road traffic accidents (29,906 people of a population of 66.4 million) and 3 in 100,000 of that total were killed (1,784 people). The UK has the third lowest road traffic accident death rate after Norway (2 in 100,000) and Switzerland (3 in 100,000) in Europe. The USA with 11 in 100,000 has the highest death rate from countries in the following list (listed from lowest to highest).
        • Norway, Switzerland, United Kingdom, Northern Ireland, Denmark, Irish Republic, Sweden, Japan, Israel, Malta, Spain, Netherlands, Germany, Finland, Slovakia, Slovenia, Australia, Austria, Canada, France, Estonia, Iceland, Belgium, Italy, Portugal, Luxembourg, Lithuania, Cyprus, Czech Republic, Greece, Hungary, Republic of Korea, Poland, Latvia, Croatia, New Zealand, Serbia, Romania, Bulgaria, USA.
      • For information about understanding risks and the difference between ongoing risks (e.g. obesity, regularly drinking alcohol, not exercising, etc) and more event based risks (e.g. riding a motorbike, having an x-ray, flying, etc) see the following link:

      • The section below considers Covid-19 risk as another example of a day to day risk (since 2019) and was added for comparative purposes. However this section rather mushroomed as the pandemic unfolded and more and more scientific research was published and Covid-19 and its risk evolved. After this significant diversion a do however get back to alcohol further below.




      • Risks and 12-month burdens of incident post-acute COVID-19 cardiovascular outcomes compared with the contemporary control cohort.
                      • Outcomes were ascertained 30 d after the COVID-19-positive test until the end of follow-up. COVID-19 cohort (n = 153,760) and contemporary control cohort (n = 5,637,647). Adjusted HRs and 95% CIs are presented. The length of the bar represents the excess burden per 1,000 persons at 12 months, and associated 95% CIs are also shown. Source:

      • Risks and 12-month burdens of incident post-acute COVID-19 cardiovascular outcomes compared with the contemporary control cohort by care setting of the acute infection.
                      • Risks and burdens were assessed at 12 months in mutually exclusive groups comprising non-hospitalized individuals with COVID-19 (green), individuals hospitalized for COVID-19 (orange) and individuals admitted to intensive care for COVID-19 during the acute phase (first 30 d) of COVID-19 (blue). Outcomes were ascertained 30 d after the COVID-19-positive test until the end of follow-up. The contemporary control cohort served as the referent category. Within the COVID-19 cohort, non-hospitalized (n = 131,612), hospitalized (n = 16,760), admitted to intensive care (n = 5,388) and contemporary control cohort (n = 5,637,647). Adjusted HRs and 95% CIs are presented. The length of the bar represents the excess burden per 1,000 persons at 12 months, and related 95% CIs were also presented. Source:

      • When considering risks, such as that for Covid-19, it is important to understand that the risk of getting Covid-19 and its impact varies over time and involves a complex set of interplaying factors both non pharm logical and pharma logical. This is nicely demonstrated in the following charts which show the evolution Covid-19 for the population as a whole in Italy over the first 2 years of the Covid-19 pandemic and the evolution of significant risks that result from infection.

                  • First chart. Epidemiological profile of the SARS-CoV-2 epidemic in Italy.
                    • a Mean estimates of the net reproduction number Rt as obtained from epidemic curves of symptomatic cases by date of symptom onset collected by the National Integrated Surveillance System (23) (mean, grey solid line; shaded area, 95% CI; y-axis on the left). Horizontal dotted line: epidemic threshold (Rt = 1). Grey bars represent the daily incidence per 1,000 individuals of SARS-CoV-2 confirmed infections by date of diagnosis as reported to the Italian Integrated Surveillance System (24,25) (y-axis on the right). Background colors indicate the classification in different phases, and the dates indicated within the graph denote the day of transition between consecutive phases. The vertical dotted line denotes the start of the vaccination campaign on December 27, 2020. b Daily number of vaccine doses administered in Italy per 1,000 individuals (stacked barchart, y-axis on the left) (22). Line and bar colors, from lighter to darker shades, indicate respectively first, second and booster doses. Solid lines show the cumulative vaccination coverage in the Italian population (y-axis on the right). In Italy, administration of two doses is recommended to all individuals aged 5 years or more; administration of one booster dose is recommended to all individuals aged 12 years or more.
                  • Second chart. Probabilities of adverse outcomes given SARS-CoV-2 infection.
                    • a Probability of being hospitalized in the different epidemic phases (%), computed as the ratio between the number of COVID-19 hospital admissions reported to the Italian Integrated Surveillance System and the estimated number of SARS-CoV-2 infections in the same phase. b Probability of being admitted to an ICU in the different phases (%), computed as the ratio between the number of SARS-CoV-2 admissions to ICUs reported to the Italian Integrated Surveillance System and the estimated number of SARS-CoV-2 infections in the same phase. c Probability of death in the different phases (%), computed as the ratio between the number of COVID-19 deaths reported to the Italian Integrated Surveillance System and the estimated number of SARS-CoV-2 infections in the same phase. d Estimated relative reduction in the probability of hospitalization in the different phases compared to the first ancestral phase (%). e As d but for the probability of ICU admission. f As d but for the probability of death. Bars: mean estimates; vertical lines: 95% CI; n= 300 stochastic model realizations. Source:


      • Duration of effectiveness of vaccines against SARS-CoV-2 infection and COVID-19 disease.
        • 18 studies were included (all studies were carried out before the omicron variant began to circulate widely).
                  • Duration of vaccine effectiveness for single-variant or non-variant-of-concern settings or mixed-variant settings.
                    • Duration of vaccine effectiveness for single-variant or non-variant-of-concern settings (A) or mixed-variant settings (B). The lower bound of 95% CIs when vaccine efficacy or effectiveness is equal to 100% were undefined in manuscripts (n=1 in panel A and n=2 in panel B), and are shown here approximated. Source:







      • When considering risks, such as that for Covid-19, it is also informative to also consider the risks associated with any mitigating factors such as the side effects of vaccines.
        • Safety of the fourth COVID-19 BNT162b2 mRNA (second booster) vaccine.
                    • Self-reported reactions and physiological reactions to the second booster dose compared with the first booster dose.
                      • Reactions to the second booster, as recorded by the smartwatches (A, B). The figures show the mean difference between the baseline period and period after vaccination for heart rate (n=570; A) and heart rate variability-based stress (n=567; B). Mean values are depicted as solid lines and 95% CIs are presented as shaded regions. Boxplots of the differences between the daily mean changes in the smartwatch indicators for heart rate (n=363; C) and heart rate variability-based stress (n=358; D) between the second and first booster. Each change is between the period after vaccination and the baseline periods. Each green dot represents a single participant. (E) A comparison of the reactions reported by participants between the first and second boosters (n=392). The bars represent the percentage of participants who reported a reaction. Error bars represent 95% CIs. For each panel, the sample size represents the number of participants that we had sufficient data points to conduct the analysis using the criteria presented in the methods section. Source:


                  • Risk of myocarditis in the 1 to 28 days after COVID-19 vaccines or SARS-CoV-2.
                    • (Left) Incidence rate ratios with 95% CIs and (right) number of excess myocarditis events for million people with 95% CIs in the 1 to 28 day risk periods after the first, second, and booster doses of ChAdOx1, BNT162b2,and mRNA-1273 vaccine or a positive SARS-CoV-2 test in (top) a population of 42 842 345 vaccinated individuals and (bottom) younger men (age <40 age="" aged="" and="" li="" men="" older="" women="" years="" younger="">

                  • Highest myocarditis incidence from each study. Each bar represents a unique study. Data are grouped according to the number of stratifiers used. Stratifiers are sex, age, dose number and manufacturer. Each bar is labelled on the x-axis with the stratifiers unique to the study that the estimate was obtained from. The number above each bar represents the myocarditis incidence. Male (M), Dose 2 (D2), Not Applicable (NA). In studies using four stratifiers, the stratifiers Male and Dose 2 were universally applicable.




      • Weighted relative risk of alcohol for all attributable causes, by standard drinks consumed per day. Source (the same source upon which the above alcohol statistical risk was based):

              • A standard drink is equivalent to 10g of alcohol = 1.25 UK units


    • For a fantastic health data website with impressive data visualisation tools see the following link:
      • http://www.healthdata.org/data-visualization/gbd-compare 
        • For an example data visualisation that shows deaths attributable to alcohol use in the UK in 2017 by type of risk see the image below:
          • For the interactive version of the data visualisation shown in the image below see the following link (data values show as you click on various parts of the visualisation and different variables can be easily selected to show different data in the visualisation):

            • Source: Institute for Health Metrics and Evaluation (IHME). GBD Compare. Seattle, WA: IHME, University of Washington, 2015. Available from http://vizhub.healthdata.org/gbd-compare. (Accessed 12th March 2020)



    • Research about the habitual intake of alcohol and the increased risk of atrial fibrillation.

              • 10g of alcohol = 1.25 UK units





    • What is the effect of a reduction in alcohol consumption on blood pressure?
      • In people who drank two or fewer drinks per day, a reduction in alcohol was not associated with a significant reduction in blood pressure; however, in people who drank more than two drinks per day, a reduction in alcohol intake was associated with increased blood pressure reduction. Reduction in systolic blood pressure (mean difference −5·50 mm Hg, 95% CI −6·70 to −4·30) and diastolic blood pressure (–3·97, −4·70 to −3·25) was strongest in participants who drank six or more drinks per day if they reduced their intake by about 50%. Source:


    • Does a physically active lifestyle attenuate the association between alcohol consumption and mortality risk?
                    • Chart 1 - Physical activity and all-cause mortality


                    • Chart 2 - Physical activity and CVD


                    • Chart 3 - Physical activity and cancer
                      • Multivariate adjusted Cox proportional hazard ratios describing the joint associations of physical activity (PA) and baseline alcohol consumption (units per week) and Chart 1 all-cause mortality events, Chart 2 CVD events, Chart 3 cancer events in the UK Biobank (n=297 988). PA was quantified using the Metabolic Equivalent Task (MET)-mins of PA/week by multiplying the MET value of activity by the number of minutes/week. We classified participants as low PA (0-599 MET-mins/week), moderate PA (600-1199 MET-mins/week) and high PA (≥1200 MET-mins/week). Alcohol consumption categories are based on the average weekly intake of standard drinks relative to UK guidelines. In the UK, one standard drink equals to 8 grams of pure alcohol. Within guidelines: <14 above="" adjusted="" alcohol="" and="" baseline="" behaviour="" body="" consumption="" diabetes.="" diet="" double="" for="" guidelines:="" guidelines="" hypertension="" index="" interaction="" li="" mass="" mins="" model="" more:="" or="" p="0.76." pa="" sedentary="" smoking="" socioeconomic="" source:="" status="" term="" the="" units="" was="" week.="" week="">




      Genetic influences
      • An individuals genetic makeup can have a significant influence on an individuals weight and the ease by which they are able to lose / gain weight, for example, see the following process flow chart that details how certain individual genomic variants were thought may have predisposed individuals to respond differently to different types of exercise and diet. The inclusion of the information provided below is intended to provide an indication of the potential influence that your genes can have but it is an early interpretation of the science and definitely a very great oversimplification of it in this particular subject area. It is however useful for illustrative purposes to show how the principles of the science can be applied although it is important to bear in mind genetically complex areas such as weight and exercise involve very many genes and that to determine more valid genetic predispositions much more complicated algorithms than that represented below are now understood to be required.  
        • See the information below the chart for more information about how to use the flow chart (you'll need the raw data from a personal DNA test to apply it to a specific individual).

          • The original source of this chart can be found via the following link:
            • https://rockstarresearch.com/these-5-genes-predict-what-kind-of-diet-and-exercise-is-best-for-your-body-2/
            • Percentages given in the flow chart boxes above, which show composite genotype categories, represent expected frequencies from the Caucasian population in the Quebec Family Study.
              • Details of the patent application that this chart summarises the logic behind can be found via the following link:
                • https://patents.google.com/patent/WO2011063098A2/en
                  • This patent application now belongs to Orig3n.com and I'm guessing underpins one or more of their products. Again I'm guessing but as the patent was filed in 2009 presumably the algorithm has been developed somewhat since then.
                • Key information to know to understand the chart is that; SNP = Single Nucleotide Polymorphism, pronounced "snip". SNPs are nucleotide variants in specific DNA base pairs and are also often just referred to as Variants. SNPs are variants that occur in more than 1% of the population as opposed to DNA mutations that occur randomly (mutations at birth that weren't inherited are estimated to number from only between 10 to 100). Each SNP has a unique ID, such as, RS4994 (as shown in the first box in the above diagram). ADRB3 (also shown in the first box) is the gene ID which the SNP, RS4994 is part. The SNP base pair values (two of; A, T, C and G which equate to the actual DNA base nucleic acids and exist in the following four combinations; AT, TA, CG and GC) can be found in an individuals DNA test raw data file (presuming the DNA test company provides access to it, which for example, 23andMe.com does on request). The two base pair values of AA or TT (one value from each double helix DNA strand) shown for gene ADRB3 and SNP RS4994 take you one way down the decision tree at the top of the chart and all other SNP base pair values take you the other way. For a video about Variants (Alleles) and Genes see the following link:
                  • For a scientifically accurate animated depiction of DNA see the following video link:
                  • For overview videos that explains how genes exist within cells see the following links:
                  • For a video that explains that the full human genome wasn't fully sequenced until 2022 and why see the following link:
                  • For an audio podcast  that explains that the Y chromosome wasn't fully sequenced until 2023 and why see the following link:
                  • For an article about using this single human genome as the reference genome in research see the following link:
                  • For a video about the use of genetic data in forensics which also provides some wider key insights see the following link:
                  • For a video with more detail about genetic variation see the following link:
                  • The human genome has about 3 billion DNA base pairs, about 25 thousand genes (composed of sequences of DNA base pairs that contain the information needed to create proteins) and there are about 3.5 million SNPs in the average persons genome (and therefore 3 billion minus 3.5 million DNA base pairs that are the same for all humans).The DNA is stored in 23 chromosome pairs (which classifies the human genome as a diplode genome) in the nucleus of almost all the cells which make the human body (so in each cell nucleus there are 46 chromosomes in total and about 6 billion DNA base pairs in total although of course approximately 50% of the DNA is the same). Each chromosome is made up of a DNA double helix strand and each chromosome contains approximately one thousand genes. One of the DNA strand pairs was derived from the fertilising sperm DNA from your father and the other from the fertilised egg DNA from your mother which created you (via the biological process called Meiosis which made alterations to the original DNA from your father and mother). Chromosomes 1 to 22 are non-sex (autosomal) chromosomes. The 23rd chromosome contains two X DNA chromosome strands if you are a female and an X and a Y DNA chromosome strand if you are a male (the Y DNA strand originally derived from the fertilising sperm DNA that created you from your father). The Y DNA chromosome strand is much smaller than the other chromosomes with fewer than 100 genes. In addition mitochondrial DNA is stored in the mitochondria in a single circular chromosome (originally from the fertilised egg that created you from your mother) and contains 37 genes. SNPs have specific  alphabetic values in each specific genome location where they have been identified.  As with all DNA base pairs they are derived from 3 possible alphabetic value combinations derived from the 2 alphabetic values possessed by each parent. Non variant DNA base pair values in SNP locations are referred to as normal or wild type and if you have a single SNP value this is called heterozygous (so two different DNA base pair values in each chromosome, one of which is a SNP) and if you have two of the same SNP values this is called homozygous.



                    • Rather than manually searching a raw DNA test data file (with the inherent base pair values interpretation confusion that can result from such an approach, as A = T and C = G and different services use different lettering standards) it is easier and will be much more incite full, to use the very impressive free services that can be accessed via the following links:
                      • codegen.eu
                      • https://impute.me/
                      • But be warned, although the services are straightforward to use, interpreting and understanding the information provided is complicated and requires a significant amount of time if you are new to the science.
                    • Alternatively or in addition if you are prepared to upload your data and have it added to a commercial or non commercial research database (such as can be accessed from the following link) they may provide their service to you for free:
                    • Alternatively or in addition you could use a commercial service to provide an analysis report for you via one of the personal genetic testing companies e.g. 23andMe or if your interest is more specific such as is in the area of nutrition / fitness / health span see the following link for an example organisation:
                    • You should however be aware that services differ significantly in what they offer and what areas of genetics they cover so if your interest is in a specific area you will need to check they cover the area you are interested in. They also vary in how up to date their reports are with regards the latest research and what analysis data sets are available to them so to get up to date and comprehensive results you may need to use multiple services. 
                    • For further information about SNPs see the following links:
                    • For a clear and short (free to access via a PDF download) example chapter about SNPs and genetics and hair colour from a book about genetics see the following link:
                    • For a video about genetic variation in a single gene in this case the APOE gene go to the memory chapter in the video via the following link:
                    • For a clear article about how one of the big genetic testing companies goes about determining your likelihood of having a genetic influenced health condition (in this instance using gout as an example) see the following link:




                        • For example  from the above link the Risk of developing schizophrenia when polygenic score is average or high (top 1%) is diagrammatically shown below:





                    • A hierarchy of observational and experimental data. Mendelian randomisation studies sit at the interface of experimental and observational studies. Their findings can be used to provide more reliable evidence to guide interventional research and provide information about potential public health interventions when a randomised controlled trial may not be feasible. Although we adapt the conventional pyramid of evidence for presentation purposes, we consider that triangulation of findings from different study designs should be used. Source:





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