Mike Allen Nov 9 (AXIOS)

Sean Parker unloads on Facebook "exploiting" human psychology

... the clarion call to seek a 'life' not a 'like'? Facebook should come with a mental and social health warning?

• "The thought process that went into building these applications, Facebook being the first of them, ... was all about: 'How do we consume as much of your time and conscious attention as possible?'"

• "It's a social-validation feedback loop ... exactly the kind of thing that a hacker like myself would come up with, because you're exploiting a vulnerability in human psychology."

• "The inventors, creators — it's me, it's Mark [Zuckerberg], it's Kevin Systrom on Instagram, it's all of these people — understood this consciously. And we did it anyway."

• "When Facebook was getting going, I had these people who would come up to me and they would say, 'I'm not on social media.' And I would say, 'OK. You know, you will be.' And then they would say, 'No, no, no. I value my real-life interactions. I value the moment. I value presence. I value intimacy.' And I would say, ... 'We'll get you eventually.'"

And, (Fast Company) Dec 11 Former Facebook exec: Social media is ripping apart society

"Facebook’s former vice president for user growth Chamath Palihapitiya recently gave a talk at the Stanford Graduate School of Business."

“The short-term, dopamine-driven feedback loops we’ve created [including the hearts, likes, and thumbs up of various social media channels] are destroying how society works.” He added, “[There’s] no civil discourse, no cooperation; [only] misinformation, mistruth. And it’s not an American problem–this is not about Russians ads. This is a global problem.”

"Unsurprisingly, when it comes to social media, his children “aren’t allowed to use that shit.”

A 'heads-up' from the horse's mouth were there ever one.

The European Prospective Investigation into Cancer and Nutrition (EPIC) study is one of the largest cohort studies in the world, with more than half a million (521 000) participants recruited across 10 European countries and followed for almost 15 years.

Rationale and Study Design (Riboli E and Kaaks R; International Journal of Epidemiology 1997; 26 (Suppl. 1): S6–S14).

Methods. EPIC is a multi-centre prospective cohort study designed to investigate the relation between diet, nutritional and metabolic characteristics, various lifestyle factors and the risk of cancer. The study is based in 22 collaborating centres in nine European countries and includes populations characterized by large variations in dietary habits and cancer risk. Data are collected on diet, physical activity, sexual maturation and reproductive history, lifetime consumption of alcohol and tobacco, previous and current illnesses and current medication. Following a common protocol and using identical equipment, blood samples are collected, aliquoted into plasma, serum, white blood cells and erythrocytes, and stored in liquid nitrogen at –196°C for future laboratory analyses on cancer cases and matched healthy controls. Anthropometric measurements are taken according to a standard protocol. It is planned to include around 400 000 middle-aged (40 - 69) men and women.

Muller et al. BMC Medicine (2016) 14:87. DOI 10.1186/s12916-016-0630-6

Note that while this observational study is prospective, it is not controlled and therefore remains subject to chance, bias and confounding.

"20% of men and 11% of women in Europe (15 countries in the European Union, EU15) who reach the age of 40 can be expected to die prematurely based on current mortality rates." There exists an estimated incidence of death prior to age 70 years among an otherwise healthy non-smoking population is approximately 4%.

Comparison of population attributable fractions (AF) from the Global Burden of Diseases (GBD) analysis with those from the present EPIC analysis. Estimates from the GBD are taken from the website http://vizhub.healthdata.org/gbd-compare. They are the estimated attributable fractions for death in Western Europe for the age range 50–69 years for each risk factor.

Population attributable fractions (%, 95% CI) GBD / EPIC

Tobacco smoking: 25 (22–27) / 31 (31 – 32)
Dietary risks (poor diet, low fresh fruit / vegs): 23 (21–26) / 14 (12 – 16)
High blood pressure: 15 (13–17) / 9 (7 – 11)
High body mass index (>30): 14 (12–15) / 3 (2 – 5)
High waist-to-hip ratio (fat distribution): 10 (8 – 12)
Physical inactivity / low physical activity: 9 (8–11) / 7 (5 – 9)
High alcohol use (2 - 6 standard drinks day): 8 (7–9) / 4 (3 – 4)

Difference between GBD and EPIC risk estimations are explained in the paper: "There are three possible explanations for these differences. Firstly, the estimates of relative risk used in the calculations might differ – indeed, we estimated modest relative risks for overweight and obesity and physical inactivity. Secondly, the distribution of the risk factors used for the GBD computations might differ from the distribution in EPIC which, for example, includes relatively few very heavy consumers of alcohol or very obese participants. This is a well-known phenomenon in prospective cohort studies, also called “healthy volunteer” effect. Finally, the reference or counterfactual distributions used for the AF calculations might differ. For instance, the GBD used a “theoretical minimum-risk exposure distribution”. On the other hand, we have chosen to not necessarily use a theoretically “optimal” exposure distribution in all cases."

Risk may be combined, eg. (EPIC) poor diet (14%) + inactivity (7%) + overweight (3%) = 24%. It is also important to remember that expressions of risk are relative, not absolute and that the EPIC study employed, "Flexible parametric survival models to model risk of death conditional on risk factors, and survival functions." "Attributable fractions (AF) for deaths prior to age 70 years were calculated based on the fitted models."

"AF's and survival functions cannot be interpreted as the expected effects on mortality if individuals were to change their lifestyle or diet, but rather reflect comparisons of individuals with a given, constant pattern of exposures, or hypothetical scenarios in which no-one in the population is exposed to a given risk factor."

It should also be borne in mind that the EPIC quantification of smoking status appears to rely on the facile classification of smoking status of 'never', 'former', or 'current smokers'. For a considerably better and more accurate understanding of this widespread and recurrent institutional and epidemiological weakness see: Assessment of Cigarette Smoking in Epidemiologic Studies. Weitkunat R, et al. Beiträge zur Tabakforschung International/Contributions to Tobacco Research Volume 25;No. 7:September 2013