A computer implemented method of determining an optimum wellness regime that best meets one or more wellness goals of a user, wherein the wellness regime comprises one or a combination of a nutrition plan, fat loss plan, muscle building plan, strength training plan or microbiotic supplement plan, and wherein the wellness goal comprises fat loss, muscle building, endurance training, cardiovascular improvement, rehabilitation from illness or disease prevention, said method comprising the steps of: a) identifying one or more traits, said traits being one or more physiological, behavioural or biological states of the user that are potentially relevant to the wellness goals, wherein the traits include one or more of insulin sensitivity; obesity risk; gut microbiome profile; blood testosterone levels; dyslipidaemia, lactose intolerance, blood triglycerides level, blood glucose levels, oxidative muscle dominance, saturated fat level, satiety, folate metabolism, homocysteine levels, methionine levels, caffeine metabolism, hypertension levels, omega 6 intake or omega 3 to 6 ratio, circadian rhythm, sleep disturbance, trainable VO2 max, salt sensitivity, workout recovery between workout sessions, workout recovery during a workout session, lactate clearance levels, basal metabolism, lean body mass, endurance capability, power capability, conscious restraint, binge eating propensity, emotional eating propensity, eating behaviour and body fat; b) identifying one or more genetic variants of the user that are relevant to one or more of the traits wherein the genetic variants include one or more: polymorphisms and/or insertions and/or deletions and/or gene copy number variants; c) identifying one or more environmental factors of the user that are relevant to said one or more of the traits wherein the environmental factors comprise height, weight, age, blood pressure, body fat percentage and fitness activity; d) assigning a weighting to each identified genetic and environmental factor for the one or more traits, said weighting defining the likely effect that the genetic and environmental factors have on the traits; e) calculating a trait score by assigning for each trait a default score indicating the average score for the general population, wherein the default score is modified based on the compound genetic and environmental weightings from step d) for each trait, each trait score giving a personalised readout for the user for that specific trait; f) defining a trait profile for the user from the trait scores, wherein the trait profile is calculated from the hierarchical, synergistic, additive, subtractive or antagonistic interaction of the trait scores said trait profile characterizing the user's likely biological, behavioural or physiological response to a wellness regime; g) determining, based at least partly on the trait profile, a wellness regime that is optimised to the wellness goals of the user. a) identifying one or more traits, said traits being one or more physiological, behavioural or biological states of the user that are potentially relevant to the wellness goals, wherein the traits include one or more of insulin sensitivity; obesity risk; gut microbiome profile; blood testosterone levels; dyslipidaemia, lactose intolerance, blood triglycerides level, blood glucose levels, oxidative muscle dominance, saturated fat level, satiety, folate metabolism, homocysteine levels, methionine levels, caffeine metabolism, hypertension levels, omega 6 intake or omega 3 to 6 ratio, circadian rhythm, sleep disturbance, trainable VO2 max, salt sensitivity, workout recovery between workout sessions, workout recovery during a workout session, lactate clearance levels, basal metabolism, lean body mass, endurance capability, power capability, conscious restraint, binge eating propensity, emotional eating propensity, eating behaviour and body fat; b) identifying one or more genetic variants of the user that are relevant to one or more of the traits wherein the genetic variants include one or more: polymorphisms and/or insertions and/or deletions and/or gene copy number variants; c) identifying one or more environmental factors of the user that are relevant to said one or more of the traits wherein the environmental factors comprise height, weight, age, blood pressure, body fat percentage and fitness activity; d) assigning a weighting to each identified genetic and environmental factor for the one or more traits, said weighting defining the likely effect that the genetic and environmental factors have on the traits; e) calculating a trait score by assigning for each trait a default score indicating the average score for the general population, wherein the default score is modified based on the compound genetic and environmental weightings from step d) for each trait, each trait score giving a personalised readout for the user for that specific trait; f) defining a trait profile for the user from the trait scores, wherein the trait profile is calculated from the hierarchical, synergistic, additive, subtractive or antagonistic interaction of the trait scores said trait profile characterizing the user's likely biological, behavioural or physiological response to a wellness regime; g) determining, based at least partly on the trait profile, a wellness regime that is optimised to the wellness goals of the user.