Population attributable fractions of the main type 2 diabetes mellitus risk factors in women: Findings from the French E3N cohort

Abstract

We have been able to sort out and quantify the effect of various dietary and biological T2DM risk factors simultaneously in a single population, and to highlight the importance of a healthy lifestyle for primary prevention: more than half the T2DM cases could have been prevented through a healthier lifestyle.

Adherence to healthy lifestyles and incidence of diabetes and mortality among individuals with diabetes: a systematic review and meta-analysis of prospective studies

“…23 For one study that reported RRs separately for men and women, we combined both RRs using a fixed effect model before entering in the RR into the overall meta-analysis. 21 If an unhealthy lifestyle was not selected as reference category, 15 17 24 risk estimates were converted by using the method of Hamling et al . 25 If studies did not report on the linear association between lifestyle factors (increment per one additional factor) and the outcomes, we calculated the study-specific slopes and corresponding 95% CIs from the natural logarithm of the reported RRs and 95% CIs across the number of included lifestyle factor, using the method of Greenland and Longnecker.…”

“…Moreover, three additional studies investigating lifestyle indices and incident T2D are available. 9 17 18 Moreover, so far no dose-response meta-analysis has been carried out to summarise these findings.…”

Proportion of upper extremity musculoskeletal disorders attributable to personal and occupational factors: results from the French Pays de la Loire study

“…For the estimation of PAFs and their CIs, we used the method described by Spiegelman and colleagues [61] with the SAS macro, which is fully-documented and publicly available (https://www.hsph.harvard.edu/donnaspiegelman/software/par/). The CIs were estimated using the multivariable delta method [61,62] as carried out by Rajaobelina and colleagues [25]. The prevalence of the exposure and adjusted RRs were considered in PAF estimates.…”

“…In this context, the effect of a particular risk factor depends not only on the strength of the association between the risk factor and the disease, but also on the prevalence of the risk factor. Nevertheless, when associations between a disease and a risk factor are assessed using classical statistical measures (relative risk or odds ratio), the population effect of some factors associated with high values of these estimates may be overestimated if few people are actually exposed to these factors [25,26]. Confounding issues should also be considered in the assessment of a risk factor effect due to the multifactorial origin of disease.…”

“…The partial PAF is appropriate when the disease of interest is multifactorial, and other risk factors are not expected to change as a result of the hypothetical intervention [36]. This contribution assessment method of some risk factors to the disease burden at the population level is widely used in studies of cancer [37][38][39][40][41][42][43][44], diabetes [25], cardiovascular disease [45,46] and hypertension [47] studies.…”