In this cross-sectional study, FINDRISC had a good performance in identifying UT2DM and MS in the working population (Office workers, instructors, and cleaners) of the LU Campuses, but a poor performance regarding prediabetes.
Comparison with other studies
Prevalence of UT2DM, prediabetes, and MS
The prevalence of UT2DM and prediabetes in our study was 7.6% and 22.9% respectively. However, a recent study carried out in the Bekaa, which is a rural area in Lebanon (26) found that the estimates of diabetes and prediabetes were 26% and 8.5% respectively using a sample of 200 individuals. Nevertheless, the prevalence of diabetes and prediabetes was reported to be 15% and 40.3% respectively in the Greater Beirut Area in a sample of 501 people (9). These findings indicate that the prevalence of both diabetes and prediabetes are high in different Lebanese settings. As for MS prevalence, it was estimated to be 36% among LU employees. Similarly, a recent cross-sectional study has been carried out in Notre Dame University employees on the three campuses (Zouk Mosbeh, North and Al Chouf) and found that 23.5% of the participants were suffering from MS (27). These findings are alarming, suggesting that LU employees are, in general, unaware of their health status which is highlighted by a low percent of physical activity practice (85%) (28), high waist circumference especially for men (102.8±12.1cm) (29) and an overweight population (30). These factors have been largely discussed and identified as risk factors for diabetes and 'metabolic syndrome' and associated health problems. Thus, the importance of the FINDRISC use among them is highlighted.
Performance of FINDRISC in detecting UT2DM, prediabetes and MS
Originally, the FINDRISC questionnaire was developed longitudinally as a future predictor of diabetes in the Finnish population (20) and was validated from a multivariate logistic regression model five years later. It was subsequently cross-sectionally validated using a maximum score of 26 (31). Later on, it has been assessed in a cross-sectional manner in several Asian (32–34), European (35–42), and American countries (43–45). In these studies, the optimal cut-off points for detecting UT2DM varied widely from 8.5 to 17 with a sensitivity ranging from 48% to 84% and a specificity ranging from 30.9% to 95%. Also, the AUROC went from 0.569 to 0.88. This vast variability indicates the need for assessing the tool within its target population.
In this study, FINDRISC had a good discriminative ability for detecting UT2DM with an AUROC value of 0.795 (0.822 in men; 0.725 in women) and a threshold value of 11.5 (10.5 in men; 11.5 in women). Besides, it’s also good at detecting MS in both men and women with an AUROC of 0.7 (0.713 in men; 0.708 in women) at a threshold of 10.5 (9.5 in men; 10.5 in women). Whereas, this ability gets weaker in case of prediabetes as evidenced by an AUROC of 0.621 (0.648 in men; 0.59 in women) especially in women. Several studies showed similar values and also confirmed that FINDRISC performed better in detecting UT2DM and MS than prediabetes. In a previous cross-sectional study on the general population of the United States of America (45), the AUROC for UT2DM was 0.75 (0.74 in men; 0.78 in women) with an optimal cutoff value of 11 in men and 12 in women, while the AUROC for prediabetes was 0.67 (0.66 in men; 0.7 in women) with an optimal cutoff of 9 in men and 10 in women. Likewise, in the Philippines (32), FINDRISC was good at predicting T2DM with an AUROC of 0.738 (0.749 in men; 0.734 in women) but failed to screen for prediabetes (AUROC = 0.562). Similar trends were noticed in the original FINDRISC study regarding the performance of the tool in detecting the three outcomes (31). In other words, the AUROC for MS discrimination was 0.72 in men and 0.75 in women. However, the optimal cutoff values for detecting T2DM and prediabetes were both 11 with lower sensitivities and specificities than the ones found in this study, and the optimum cutoff for MS was not established. Similarly, FINDRISC was also found to perform well in the detection of MS (AUC = 0.77) in Taiwanese (46), but the optimal cutoff point was not reported. One previous cross-sectional study in Greece (35) reported a threshold for MS of 15 which is higher than the one reported in our study. However, it is well known that prediabetes which is a combination of excess body fat and insulin resistance, is considered an underlying etiology of MS (47). In turns, MS is considered as a risk factor for T2DM (48) which may explain why 70% of people with prediabetes in this study had MS (P < 0.0001) and 76% of those with UT2DM had MS and that’s why the threshold for MS is localized between the thresholds for prediabetes and UT2DM in our community. To date, only one study assessed the predictive ability of FINDRISC in detecting incident cases of MS (AUC = 0.65) rather than prevalent cases at a cutoff of 12 (49).
It is also worth mentioning that men had always higher AUROC values as well as lower cutoff values than women, specifically for UT2DM and MS in the current study. In other words, men tend to have more risk factors putting them at a higher risk for diabetes, prediabetes, and MS which improves the predictive ability of FINDRISC when compared with women and increases their scoring in FINDRISC and thus limiting their threshold to lower values. In this study, a synergistic interaction for the combined BMI (p < 0.0001), WC (p < 0.0001), smoking (p < 0.0001), could renders men more prone for diabetes with higher prevalence for UT2DM (p = 0.001) and MS (p < 0.0001)
The usefulness of FINDRISC as a screening tool among LU workers
The advantage of the FINDRISC relies on its self-report questions so that LU workers that reported to be extremely busy because of their work and daily life stressors can find it easier to fill the FINDRISC quickly and rate their current health status. Being at higher risk based on FINDRIC score would be a sufficient trigger for them to start applying lifestyle changes or to seek health professionals’ help.
Strengths and limitations of the study
Some limitations warrant considerations. First, a misclassification bias could be introduced because the diagnosis of diabetes of the respondents was self-reported. Further, the diagnosis of diabetes and prediabetes of the included participants was not confirmed by repeat testing on a separate day as recommended (14). However, these tests may pose additional costs on our limited budget. Second, a selection bias could be present as the participants were drawn only from LU campuses and, thus, the results may not be generalizable to the rest of the Lebanese citizens living in other settings. Third, we could not assess the ability of the FINDRISC to catch the future risk of having diabetes and MS as it was tested in some longitudinal studies (49-51)
This study has also considerable strengths. To our knowledge, this is the second study that has been carried out in an Arabic country in the Middle East region which has investigated the validity of FINDRISC. A previous study was conducted in Kuwait and showed similar results (33). Additionally, a recent Jordanian study pointed out the usefulness of FINDRISC to screen for type 2 diabetes in a young student population but didn’t have the opportunity to validate it (52). Second, a selection bias was avoided since our sample was fairly divided between men (44.8%) and women (50.2%) and thus the gender differences in the study outputs are not biased. Third, the diagnosis of diabetes was done based on a combination of two plasmatic tests as it is ideally recommended which are the FBG and OGTT. Thus, the misclassification bias would be lessened, and the estimation of the risk of T2DM as well as the performance of FINDRISC are optimized.
Conclusion and perspectives
This cross-sectional study has successfully demonstrated that FINDRISC could be useful as a first-line screening tool that identifies employees with UT2DM, prediabetes, and MS that might benefit from lifestyle modification. FINDRISC model could be also beneficial for community-based interventions and screenings as well as in clinical practice by the health professionals. In future studies, FINDRISC should be validated on a larger and more representative sample of the Lebanese population so Lebanese citizens living in a resource-poor setting like rural areas would benefit the most. Also, FINDRISC should be assessed in a longitudinal study who allows the identification of incident cases of diabetes and MS rather than prevalent cases.