Anti-Depression Medication Taking and Risk of Metabolic Syndrome among US Citizens Aged 60+ years: an Across-sectional Analysis of the NHANES 2007-2008

Available epidemiological evidence suggests that depression among the elderly is a significant public health problem both for its effect on quality of life and for its impact on expected lifespan^{1, 2}. With an estimated prevalence of 4% among the US household population aged 60+, approximately 2.5 million in this age group suffer from depression based on 2010 – 2014 American Community Survey estimated figures ³. Moreover, depression in seniors is considered as one of the most common conditions associated with suicide. Although people aged 60+ comprise only 19.5 percent of US population in 2014, they accounted 25.5 percent of total suicide deaths ⁴. In that year, 18.6 of every 100,000 people aged 60 and older died by suicide; it is significantly higher than the rate of 13.4 per 100,000 in the general population.

There is no doubt that medication treatment for seniors with serious depression is important and necessary. However, seniors are often with large degree of medical co-morbidity, especially vascular diseases, or with much unfavorable profile of inflammatory and metabolic dysregulations, which may contribute to the development of depression in late life ^{5, 6, 7, 8, 9, 10}; while antidepressants use are often associated with weight gain and metabolic abnormalities ^{11, 12, 13}. As drug therapy is often selected as a primary mode of management in depression and the antidepressants now rank as the most frequently dispensed prescription medication in the US ¹⁴, the risk for metabolic syndrome (MS) among seniors is particularly a concern. MS is a clustering of risk factors known to promote or increase the risk of cardiovascular disease including impaired glucose metabolism, hypertension, dyslipidemia and abdominal obesity ^{15, 16, 17}. Thus, it is necessary to be caution in regarding using antidepressants among the elderly to minimize cardiovascular risk. However, it seems no study only focus on seniors to examine how MS and its risk profile are affected by taking antidepressant drugs and whether using anti-depressant drugs is the only explanation for the observed cardio-metabolic risk association with using anti-depressant drugs. In this study, using the National Health and Nutrition Examination Survey (NHANES) 2008 dataset, we explored whether such an association can be identified.

Overall, approximately 80% of males and 86% of females reported taking prescribed medications during the prior month, with 6% of males and 16% of females respectively having used anti-depressants. Among those who reported taking anti-depressant drugs, approximately 82% of them were on selective serotonin reuptake inhibitors (SSRIs). Characteristics of the sample selected for analysis are shown in Table 1. Gender differences were few in statistically significance. Females were slightly older (69.9 years vs. 68.2 years), had a lower proportion of persons married or living with a partner (51.2 % vs. 75.4%), and higher proportion of taking antidepressants (16.2 % vs. 5.7%).

Table 2 provides a breakdown of subjects by gender, prescription medication use and prevalence of variables associated with MS. Anti-depressant drug users were marginally younger in females compared with non-drug and other drug users, while marginally older among males. The other selected characteristics were similar between groups by gender except that the proportion of non-Hispanic white in female anti-depressant drug users were much higher than other groups. Prevalence rates of MS were quite similar between the two drug use subgroups in females (41.7% for other drug users vs. 40.7% for anti-depressant drug users), but slightly lower in males with using anti-depressant drug (43.0% vs. 35.2%). Not surprisingly, those not taking any form of prescription medication were less likely to have MS, in particular among men (10.8% for males and 33.8% for females). Duration of drug exposure was positively related to anti-depressant use in males. When on antidepressants, the average duration of use was 10.5 years compared with 8.2 years for those solely on other drugs. No such difference appeared for females (12.0 years vs. 12.2 years).

Table 3 presents the results of logistic regression analyses designed to measure adverse metabolic affects which may be associated with anti-depressant use. The results from model 1 indicated that after adjusting for age, sex and ethnicity, prescription drug use was associated with an increased odds for MS whether on anti-depressants (odds ratio (OR, 95% CI):2.25 (1.07, 4.69)) or off (2.73 (1.96, 3.82)). When further adjusting for other covariates (model 2 and 3) the results were similar. Those who took anti-depressants were from two subgroups, i.e., a) the duration of taking non-anti-depressant medications is longer than that of taking anti-depressant medications, and b) taking antidepressants alone or its duration is longer than that of taking non-anti-depressant medications. However, when further dividing those who took anti-depressants into two subgroups in the models, the results were similar to Table 3 except none of them reached statistical significance (data not shown). The risk associations between prescribed drugs and each component of MS were also examined. The same covariates as in the previous model 3 were included in the logistic regression analyses. Compared to those non-drug users, prescription drug use, with or without anti-depressants, was associated with a statistically significant rise in the odds for diabetes (5.29 (2.81, 9.90) for those without anti-depressant drugs and 3.73 (1.12, 12.50) for those with anti-depressant drugs) and elevated blood pressure (8.40 (4.93, 14.30) for those without anti-depressant drugs and 5.30 (2.80, 9.70) for those with anti-depressant drugs). The ORs of having high waist circumference were similar for both drug users (OR = 1.90), but only non-antidepressant reached statistical significance. The OR estimates for the remaining variables (TG, HDL) were increased by drug use relative to the non-user reference group; however, neither reached statistical significance. No excess risk on any of the variables was found for anti-depressant drug users relative to non-antidepressant drug users, i.e., Group 3 versus Group 2.

To generate the results in Table 4, we used a surrogate measure of drug exposure as described in the Methods section above. No increased odds of MS was evident as a result of relatively prolonged exposure to anti-depressants where non-antidepressant drug users became the referent.

The prevalence of depression detected by the PHQ-9 screening tool (PHQ-9≥5) was 8.6% for males and 11.4% for females among group 1 (non- users) and 14.1% for males 16.7% for females among group 2 (non-anti-depressant drugs in the prescribed medications). Compared to a group who screened negative for depression (PHQ-9<5), the OR (95%CI) of MS was 1.16 (0.90, 1.49) for PHQ-9 ≥5 (mild or more severe depression) and 1.06 (0.44, 2.56) for PHQ-9≥10 (moderate or more severe depression).

Using the NHANES 2007-08 data we examined the cardio-metabolic risk association with anti-depressants drug use among US seniors and found that in comparing to no drug users, seniors with prescribed anti-depressants were in more than two times higher odds of having MS. The high odds of MS association with using anti-depressant drugs have been observed by several different studies ^{12, 13, 20}. For instance, results from the PPP-Botnia Study conducted among Finns aged 18-75 years indicated that users of anti-depressant drugs had more than 50% higher odds of MS in comparing to non-users ¹², and the cohort study conducted in Italy showed that in the general population without treated cardiovascular risk, pharmacologic treatment for depression was associated with about two-fold higher risk in all-cause mortality and major cardiovascular outcomes²⁰. However, the observed cardio-metabolic risk association in our study seems not to be explained well as the result of taking antidepressants because in comparing to those who were not on any prescribed drugs, the seniors with antidepressants had a similar level of odds of MS as those with non-anti-depressant drugs. In addition, the cardio-metabolic risk profiles were very similar between these two groups; in general, both of them had much higher odds of diabetes and hypertension in comparing to non-drug users.

Although results from some other studies suggested that the increased cardio-metabolic risk may be associated with the severity of mental health status^{13, 21}, our results from those who were not on antidepressants, however, failed to support the association. It seems the odds of having MS for those with depression measured by PHQ-9 score equal or higher than five was similar to those with a score less than five. The different results could be due to the differences between our study and others on age of the study subjects (ours were aged 60+ vs. others were with much wide age ranges) and the evaluation methods (we examined the MS risk association with depression only among those who did not take anti-depressants, while other studies did not exclude them).

However, results from some studies indicate an alternative direction that depression, in particular seniors’ depression, may be contributed by their cardio-metabolic abnormality. The term "vascular depression" has been proposed to describe a subset of depressive disorders that occurs in old age as a consequence of cerebrovascular disease^{5, 22}. It has been estimated that approximately 3.4% or 2.64 million American adults 50-years and older might be considered having vascular depression²³ and treating late-life depression could improve cognitive function²⁴. The change of white matter lesion volume is considered to have a causal association with vascular depression²⁵, but it seems more research is needed to explore the bi-directional relationship between depression and vascular disease²⁶.

Several limitations should be aware when interpreting the results from this study. First, like any cross-sectional study, the observed relationship cannot be explained as a causal relationship. Second, the depression measured with PHQ-9 screening tool score among those without taking anti-depressant drugs may not be so sensitive. However, the questionnaire has been validated and applied in many larger population studies; using it as a screening tool to identify the possible depression cases is still useful. Third, the prescribed medications and their duration were self-reported. Although the majority of these medications were verified with the medication containers it might still have some misclassification. The durations particularly for those seniors who took multiple medications might be less accurate. Furthermore, it was difficulty to examine the truly impact of antidepressants on MS due to the small size in that group, which was mixed with people who took the medications for depression at the first place and people who took it after other health problems. Nevertheless, the strengths of the study include the exclusion of those with serious disease history, such as CVD and cancer, the standardized measurements of MS components, detail information on demographic and potential confounding variables, and the data quality since it was from a well-organized and national representative survey.

In conclusion, seniors with prescribed medications, regardless whether taking anti-depressants or not, are more likely to have MS, diabetes, and high level blood pressure. However, the observed the cardio-metabolic risk association seems similar between seniors taking prescribed medications either with or without antidepressants. Thus, more research may be needed to explore the relationship between depression and cardio-metabolic risk among the elderly.

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