The spread of obesity in a social network

Common sense: folk wisdom that ethnobiological and ethnomedical research cannot afford to ignore

Common sense [CS], especially that of the non-scientist, can have predictive power to identify promising research avenues, as humans anywhere on Earth have always looked for causal links to understand, shape and control the world around them. CS is based on the experience of many individuals and is thus believed to hold some truths. Outcomes predicted by CS are compatible with observations made by whole populations and have survived tests conducted by a plethora of non-scientists. To explore our claim, we provide 4 examples of empirical insights (relevant to probably all ethnic groups on Earth) into causal phenomena predicted by CS: (i) "humans must have a sense of time", (ii) "at extreme latitudes, more people have the winter blues", (iii) "sleep is a cure for many ills" and (iv) "social networks affect health and disease". While CS is fallible, it should not be ignored by science - however improbable or self-evident the causal relationships predicted by CS may appear to be.

Talking with others about stigmatized health conditions: implications for managing symptoms

We investigated the influence of social ties on symptom management and help seeking, using urinary symptoms as a case study. Talking with others about these symptoms was common and both facilitated and hindered symptom management and help seeking. In some cases, talking with others resulted in gaining a sense of identification with others suffering the same symptoms, receiving assistance to ease the burden of symptoms, obtaining suggestions to help manage symptoms, and learning information about available treatments. In other cases, talking with others served to normalize symptoms to such an extent that individuals saw no need to manage their symptoms differently.

Sensitivity analysis for contagion effects in social networks

Analyses of social network data have suggested that obesity, smoking, happiness and loneliness all travel through social networks. Individuals exert "contagion effects" on one another through social ties and association. These analyses have come under critique because of the possibility that homophily from unmeasured factors may explain these statistical associations and because similar findings can be obtained when the same methodology is applied to height, acne and head-aches, for which the conclusion of contagion effects seems somewhat less plausible. We use sensitivity analysis techniques to assess the extent to which supposed contagion effects for obesity, smoking, happiness and loneliness might be explained away by homophily or confounding and the extent to which the critique using analysis of data on height, acne and head-aches is relevant. Sensitivity analyses suggest that contagion effects for obesity and smoking cessation are reasonably robust to possible latent homophily or environmental confounding; those for happiness and loneliness are somewhat less so. Supposed effects for height, acne and head-aches are all easily explained away by latent homophily and confounding. The methodology that has been employed in past studies for contagion effects in social networks, when used in conjunction with sensitivity analysis, may prove useful in establishing social influence for various behaviors and states. The sensitivity analysis approach can be used to address the critique of latent homophily as a possible explanation of associations interpreted as contagion effects.

A national study of physician recommendations to initiate and discontinue growth hormone for short stature

OBJECTIVES

Overall growth hormone (GH) use depends on decisions to both initiate treatment and continue treatment. The determinants of both are unclear. We studied how physicians decided to begin GH in idiopathic short stature and how, after an initial course of treatment, they decided to continue, intensify (increase the dose), or terminate treatment.

METHODS

We used a national census study of 727 pediatric endocrinologists involving a structured questionnaires with a factorial experimental design. Main outcome measures were GH recommendations for previously untreated children and those children who were treated with GH for 1 year.

RESULTS

The response rate was 90%. In previously untreated children, recommendations to initiate GH were consistent with guidelines and also influenced by family preferences and physician attitudes (P<.001). In children treated with GH, recommendations on whether to continue GH were influenced by the growth response to therapy (P<.01) but were divided regarding course of action. With identical growth responses to treatment, physician decisions diverged (intensify versus discontinue GH) and were driven by independent, nonphysiologic, and contextual factors (eg, physician attitudes, family preferences, and GH-initiation recommendation; each P<.001). Together, attitudinal and contextual factors exerted more influence on continuation decisions than did the growth response to therapy.

CONCLUSIONS

Physician decisions to initiate GH are largely consistent with evidence-based medicine. However, decisions about continuing GH vary and are strongly influenced by factors other than response to treatment. With a potential market of 500 000 US children and costs exceeding $10 billion per year, changes in GH use may depend on potentially modifiable physician attitudes and family preferences as much as physiologic evidence.