Lifestyle Changes in Relation to Initiation of Antihypertensive and Lipid-Lowering Medication: A Cohort Study
Authors: Juha Hartikainen
Danny Liew
Maarit J Korhonen
Soko Setoguchi
Mika Kivim√§ki
Jaana Pentti
Jussi Vahtera
Jenni Ilom√§ki
Journal: Journal of the American Heart Association (2020)
Discipline: CLINICAL MEDICINE
Keywords: antihypertensive agents; lifestyle; longitudinal; primary prevention; statins.
Affiliations: Department of Public Health University of Turku Finland., Institute of Biomedicine University of Turku Finland., Centre for Medicine Use and Safety Faculty of Pharmacy and Pharmaceutical Sciences Monash University Melbourne Victoria Australia., Finnish Institute of Occupational Health Helsinki Finland., Clinicum Faculty of Medicine University of Helsinki Finland., Heart Center Kuopio University Hospital Kuopio Finland., School of Medicine University of Eastern Finland Kuopio Finland., Rutgers School of Public Health and Rutgers Robert Wood Johnson Medical School New Brunswick NJ., School of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia., Department of Epidemiology and Public Health University College London London United Kingdom., Turku University Hospital Turku Finland.

Abstract:  Background Lifestyle modification is a key component of cardiovascular disease prevention before and concurrently with pharmacologic interventions. We evaluated whether lifestyle factors change in relation to the initiation of antihypertensive or lipid-lowering medication (statins). Methods and Results The study population comprised 41 225 participants of the FPS (Finnish Public Sector) study aged ‚â?0 years who were free of cardiovascular disease at baseline and responded to ‚â? consecutive surveys administered in 4-year intervals in 2000-2013. Medication use was ascertained through pharmacy-claims data. Using a series of pre-post data sets, we compared changes in body mass index, physical activity, alcohol consumption, and smoking between 8837 initiators and 46 021 noninitiators of antihypertensive medications or statins. In participants who initiated medication use, body mass index increased more (difference in change 0.19; 95% CI, 0.16-0.22) and physical activity declined (-0.09 metabolic equivalent of task hour/day; 95% CI, -0.16 to -0.02) compared with noninitiators. The likelihood of becoming obese (odds ratio: 1.82; 95% CI, 1.63-2.03) and physically inactive (odds ratio: 1.08; 95% CI, 1.01-1.17) was higher in initiators. However, medication initiation was associated with greater decline in average alcohol consumption (-1.85 g/week; 95% CI, -3.67 to -0.14) and higher odds of quitting smoking (odds ratio for current smoking in the second survey: 0.74; 95% CI, 0.64-0.85). Conclusions These findings suggest that initiation of antihypertensive and statin medication is associated with lifestyle changes, some favorable and others unfavorable. Weight management and physical activity should be encouraged in individuals prescribed these medications. 

Retracted: No

PubPeer comments:
 Hariyanto et al. paper is interesting because their analysis yielded cut-off values that are potentially useful. These are the results, in which the paper was based upon. However, upon reading, we notice a potential methodological fallacy. By selecting articles with only significant results in ROC analysis, will lead to bias. In systematic reviews, we have to be objective and factor in every results that supports or against our hypothesis. But even more concerning is the methodological fallacy in which the cut-off points, sensitivity, specificity, and ROC curve is based on. The method is unconventional and the authors provide study level data and treat them as individual data. If this is true, then the results are not trustworthy due to ecological bias. Moreover, each studies in meta-analysis are weighted, i.e. 10 studies did not contribute equally to the pooled effect estimate, but they are calculated based on sample size and other factors. Treating these data as if it is an individual data is misleading, because they will have same equal weight. The readers will also be interested how the authors come up with the method of pooling significant study level mean differences and generate ROC with equal weighting. We have written a letter to the editor = https: doi.org 10.1016 j.ajem.2021.03.029 In which the authors replied, While it is not common to perform receiver operating characteristic (ROC) curves on meta-analysis study, however we think that it is still possible and also methodologically valid to perform ROC curves analysis based on study-level data [3,4]. Several previously published meta-analysis have already done the same before us. They generated pooled ROC curve analysis based on sensitivity, specificity, and ROC curve of study-level data [[5], [6], [7]]. Their studies were even cited by many other studies, meaning that another authors have acknowledged the results from their studies. The reply = https: doi.org 10.1016 j.ajem.2021.03.077 Which means that the statistical analysis in this article is fundamentally flawed which lead to misleading results. The authors should be responsible for the validity of their methods. Simply copying methods and referring to other paper isn t a best practice. Fake or retracted studies may also receive a lot of citations. From the 3 papers that the authors referred to, are not methodological studies and published in COVID-19 pandemic, in which peer reviews are far from robust. Also, the authors did not follow the methods described in the two methodological papers that were cited in their reply, the methods are not validated and not widely accepted by the Cochrane Collaboration. Even though the two papers were published almost 2 decades ago. Aside from validity, the authors have not explained why they pooled only statistically significant (positive) while leaving out the negative studies from the ROC analysis. ,