Emotional disorders like anxiety and depression are common mental health conditions that cause significant distress across the lifespan. More often than not, these conditions tend to co-occur, with reports that 63% to 67% experience both anxiety and depression (Lamers, 2011). Evidence suggests that individuals with co-occurring anxiety-depression experience higher rates of recurrence, greater symptom severity, more functional impairment, and increased suicidality than those with anxiety or depression alone (Lamers et al., 2011; Ruscio et al., 2017).

In the context of co-occurrence, the temporal sequence of disorder onset (referring to which disorders develop first) may be critical in informing treatment and predicting outcomes. For example, previous research suggests that anxiety typically precedes depression (Solmi et al., 2022), meaning that experiencing anxiety may put someone at risk of developing depression.

Genetics account for up to 50% of the risk for individual anxiety disorders, but the genetic factors involved in co-occurrence remain largely unexplored. The Netherlands Study of Depression and Anxiety (NESDA; Hofmeijer-Sevink et al., 2012) is one of the only studies to have examined the outcomes of those with co-occurring anxiety disorders to anxiety-depression comorbidity and single disorders (i.e., anxiety or depression).

In the current study, Davies and colleagues (2023) attempted to replicate and extend findings from the NESDA study by further examining factors associated with anxiety disorder comorbidity. They had 3 main aims:

1. Comparing the characteristics (socio-economic status, trauma, clinical outcomes) of those with a single disorder compared to those with comorbid anxiety or depression
2. Examining the temporal sequence of the emergence of comorbid anxiety-depression
3. Investigating the genetic risk of comorbidity using either polygenic risk scores or self-reported family history of mental health diagnoses.

Methods

The authors used data from the NIHR BioResource (NBR) cohort, which included data from the Genetic Links to Anxiety and Depression (GLAD) study and the COVID-19 Psychiatric and Neurological Genetics (COPING) study. GLAD recruited participants aged 16+ and living in the UK with a lifetime history of anxiety and/or depressive disorders, whereas COPING recruited from participants from GLAD and NBR more widely.

For the current study, participants were included if they met the DSM-5 diagnostic criteria for a lifetime anxiety disorder or Major Depressive Disorder (MDD) and were excluded if any missing data impacted comorbidity group categories.

Analyses were conducted using multiple logistic regressions, adjusting for socio-economic status, trauma, and clinical characteristics.

Results

The final sample included 38,775 individuals (GLAD: n = 35,210; COPING NBR: n = 3,565) with an average age of 39. The sample was highly educated (56% had a university degree) and predominantly white (95%) and female (79%).

Of these participants:

• 92% met criteria for Major Depressive Disorder (MDD)
• 83% met criteria for any anxiety disorder
• 61% reported generalised anxiety disorder (GAD)
• 46% reported panic disorder
• 40% reported social anxiety disorder (SAD)
• 25% reported specific phobia
• 22% reported agoraphobia

Aim 1: Characteristics

Fully adjusted models compared diagnosis co-occurrence across four pairings:

1. Anxiety-anxiety vs. anxiety only (e.g., comorbid SAD and GAD vs. SAD alone)
2. Anxiety-depression vs anxiety only (e.g., comorbid GAD and MDD vs. SAD alone)
3. Anxiety-anxiety vs. anxiety-depression
4. Anxiety-depression vs. depression only

Results (presented as odds ratios and 95% confidence intervals) found that:

• In comparison to the anxiety-only group, the anxiety-anxiety group had:
  • Higher rates of self-reported anxiety or depression diagnoses (OR = 2.96, [2.19 to 4.03])
  • Younger age of onset (OR = 0.77, [0.70 to 0.84])
  • Slightly higher recurrence (OR = 1.07, [1.04 to 1.10])
  • Slightly higher levels of anxiety symptoms (OR = 1.11, [1.08 to 1.05])
• In comparison to the anxiety-only group, the anxiety-depression group had:
  • Considerably higher rates of self-reported anxiety or depression diagnoses (OR = 8.21, [6.70 to 10.05])
  • More experiences of adult (OR = 1.49, [1.23 to 1.81]) or catastrophic trauma (OR = 1.35, [1.13 to 1.60])
  • Younger age of onset (OR = 0.60, [0.56 to 0.65])
  • Slightly higher recurrence (OR = 1.03, [1.01 to 1.05])
  • Slightly higher levels of depressive symptoms (OR = 1.07, [1.05 to 1.09])
• In comparison to the depression-only group, the anxiety-depression group showed greater symptom complexity and severity, with:
  • Higher rates of self-reported anxiety or depression diagnoses (OR = 2.08, [1.82 to 2.38])
  • Slightly higher rates of self-reported other mental health diagnoses (OR = 1.34, [1.24 to 1.45])
  • Younger age of onset (OR = 0.61, [0.58 to 0.63])
  • Slightly higher recurrence (OR = 1.07, [1.06 to 1.08])
  • Slightly higher current anxiety (OR = 1.15, [1.14 to 1.16])
• In comparison to the anxiety-depression group, the anxiety-anxiety group had:
  • Younger age at baseline (OR = 0.82, [0.77 to 0.86])
  • Lower rates of adult (OR = 0.80, [0.69 to 0.91]) or catastrophic trauma (OR = 0.77, [0.67 to 0.88])
  • Fewer GCSE (OR = 0.60, [0.42 to 0.87]) and A-Level qualifications (OR = 0.62, [0.43 to 0.91])
  • More severe current anxiety symptoms (OR = 1.08, [1.06 to 1.09])
  • Less severe current depression symptoms (OR = 0.92, [0.91 to 0.94])
  • Reduced likelihood to report a diagnosed anxiety/depression disorder (OR = 0.42, [0.33 to 0.53])

Aim 2: Temporal sequence

Models examining the temporal sequence of anxiety/depression emergence showed that those in the anxiety-first group, in comparison to the depression-first group, were:

• More likely to be female;
• Less likely to have a university degree or A-Level qualifications;
• Younger age of disorder onset;
• Less likely to self-report receiving an anxiety or depressive disorder diagnosis;
• More severe current anxiety symptoms.

Aim 3: Genetic risk

Familial genetic risk analyses were not significant in the full-adjusted model. However, after accounting for all factors, anxiety-anxiety in comparison to anxiety-only was associated with higher polygenic scores for neuroticism.

Conclusions

The authors conclude that:

Our study represents the largest and most comprehensive investigation of factors associated with anxiety comorbidity to date.

Many NESDA study findings were replicated, particularly that comorbid disorders demonstrated more severe presentations than single disorders (e.g., higher symptom severity, higher recurrence). However, unlike NESDA, Davies et al. (2023) found that anxiety-anxiety comorbidities were associated with higher anxiety symptom severity than with anxiety-depression comorbidity.

The temporal sequence findings supported previous studies highlighting that anxiety disorders have an earlier onset than depressive disorders, indicating that first onset anxiety may be more common when there are co-occurring conditions (Lamers et al., 2011). Unfortunately, the genetic risk analysis was underpowered to detect any group differences, as the sample comprised a smaller subset of the total sample.

Strengths and limitations

The greatest strength of the current study is the large sample, as this improves the accuracy and reliability of the findings. However, when conducting analyses of secondary data from combined datasets, researchers have no influence over the available variables, and must use the data as best they can. As often critiqued in papers like these, some observed associations may be better accounted for by factors that were not measured and included in the model, such as early life adversity, stress, physical health problems, neurodiversity, and bullying.

Other strengths of the paper include the statistical analyses which are clearly and comprehensively described and have been made freely available to the public, demonstrating good open science practices. The analyses were also pre-registered prior to being undertaken, further enhancing the transparency of the study. The fact that one of the study aims was to replicate findings from a previous study and dataset is also a demonstration of good science and enhances the credibility of some of the findings.

However, there were some limitations:

• This study, like most psychological research, is subject to ascertainment biases, referring to when some individuals within a population are more likely to be represented than others. Most of the current sample were white, female and highly educated, which is not representative of the UK population – it is therefore unclear how generalisable these findings are.
• The GLAD cohort tend to show high rates of comorbidity, trauma, and symptom severity, meaning that the findings may not be generalisable to less severe populations (i.e., the general public).
• Most data were collected retrospectively by self-report, which could have led to inaccurate recall, particularly around age of onset and recurrence (i.e., how many historical episodes of depression or anxiety they had experienced).
• Some of the findings are difficult to interpret without further information. For example, age at onset seems to be significant in the anxiety-anxiety vs the anxiety-depression group, but the direction of effect is not readily interpreted without further clarification from the authors.
• As mentioned, the genetic risk analysis was underpowered to detect significant effects, so additional research is needed.
• Only 8% of the sample did not have MDD, meaning that comparison between anxiety-anxiety comorbidities and anxiety-only may have been underpowered.
• Finally, some of the data collection period overlapped with the COVID-19 pandemic, and it is not clear how this world event impacted the study findings.

Implications for practice

The study reinforces findings from the existing literature that, in the context of comorbid anxiety and depression, anxiety seems to have an earlier age of onset. Early identification and intervention for anxiety disorders may therefore help to prevent the developmental of other comorbid psychiatric disorders, such as depression or additional anxiety disorders. This, in turn, may reduce treatment costs in the long-term. But how can we intervene early and give people the support they need?

Two obvious avenues for early identification and treatment lie within primary care services and schools. Within primary care, it seems important that if either anxiety or depression is present, the other is also screened for – and, if identified, subsequently treated. If this is the case, transdiagnostic interventions that target similar mechanisms that are maintaining the disorders (e.g., emotional avoidance) may offer an appropriate avenue for treatment (learn more about transdiagnostic approaches to mental health in Melissa and Tim’s Mental Elf blog). In relation to schools, prevention programmes targeting anxiety and depression show some promise, with indications of a significant public health impact if implemented on a large scale. These efforts may then have a knock-on effect for other associations identified in this study, such as high recurrence and symptom severity.

On a final note, as someone who has been diagnosed with comorbid anxiety and depression, I can say that the findings of this study reflect my own personal experiences, which has felt both insightful and worrying. Either condition on its own is a lot to deal with, but imagine (at its worst) being in an almost constant state of fluctuation between hypo-arousal (i.e., numbness, fatigue) and hyper-arousal (i.e., hypervigilance, panic). Yeah – it’s a lot. Ideally, we need to find a way to prevent comorbid disorders from developing in the first place – but failing this, I think it’s important for clinicians to take an holistic approach when faced with comorbid anxiety and depression, treating the whole person, rather than simply focusing on just one disorder. Not an easy job!

Acknowledgements

I would like to thank Jeanne Wolstencroft for her contribution to this blog.

Statement of interests

None.

Links

Primary paper

Davies, M. R., Glen, K., Mundy, J., Ter Kuile, A. R., Adey, B. N., Armour, C., … & Eley, T. C. (2023). Factors associated with anxiety disorder comorbidity. Journal of Affective Disorders, 323, 280-291.

Other references

Albajara Saenz, A. (2022). Do school-based depression and anxiety prevention programmes work? The Mental Elf.

Black, M., & Dalgleish, T. (2019). Transdiagnostic approaches to mental health : Keeping the baby and throwing out the bathwater. The Mental Elf.

Hofmeijer-Sevink, M. K., Batelaan, N. M., van Megen, H. J., Penninx, B. W., Cath, D. C., van den Hout, M. A., & van Balkom, A. J. (2012). Clinical relevance of comorbidity in anxiety disorders: a report from the Netherlands Study of Depression and Anxiety (NESDA). Journal of Affective Disorders, 137(1-3), 106-112.

Lamers, F., van Oppen, P., Comijs, H. C., Smit, J. H., Spinhoven, P., van Balkom, A. J., … & Penninx, B. W. (2011). Comorbidity patterns of anxiety and depressive disorders in a large cohort study: the Netherlands Study of Depression and Anxiety (NESDA). The Journal of Clinical Psychiatry, 72(3), 3397.

Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., … & Fusar-Poli, P. (2022). Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry, 27(1), 281-295.

Ruscio, A. M., Hallion, L. S., Lim, C. C., Aguilar-Gaxiola, S., Al-Hamzawi, A., Alonso, J., … & Scott, K. M. (2017). Cross-sectional comparison of the epidemiology of DSM-5 generalized anxiety disorder across the globe. JAMA Psychiatry, 74(5), 465-475.

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