Age and sex‐related variability in the presentation of generalized anxiety and depression symptoms

Generalized anxiety and depression are extremely prevalent and debilitating. There is evidence for age and sex variability in symptoms of depression, but despite comorbidity it is unclear whether this extends to anxiety symptomatology. Studies using questionnaire sum scores typically fail to address this phenotypic complexity.


| INTRODUCTION
Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are the most common psychiatric disorders worldwide (Kessler et al., 2005;Lim et al., 2018). Around 11% of the world's population experience clinically relevant symptoms within their lifetime (Lim et al., 2018) and they co-occur simultaneously or sequentially in 50%-80% of cases (Brown et al., 2001;Jacobson & Newman, 2017;Kroenke et al., 2007;Moffitt et al., 2007). MDD and GAD are heterogeneous conditions, meaning affected individuals can present with unique symptom combinations (Fried & Nesse, 2015a, 2015b. In research, questionnaire-derived sum scores are commonly used to identify cases or measure disorder severity (Fried & Nesse, 2015b;Jokela et al., 2019;Ohannessian et al., 2017). Sum scores are a symptom count, which assumes all symptoms equally and consistently contribute to a disorder (Fried & Nesse, 2015b). They also lack information on which symptoms are present for an individual and how those symptoms interact (Jokela et al., 2019). For instance, four underlying factors of generalized anxiety and depressive symptoms were identified in the UK Biobank: anxiety symptoms, psychomotorcognitive impairment, neurovegetative states, and mood symptoms (Jermy et al., 2020). Exploring patterns of symptom co-occurrence instead of using sum scores may identify diagnostic subtypes of MDD, GAD, or their comorbid presentation, helping to refine diagnoses (Eeden et al., 2019).
The presentation of MDD symptoms varies across ages (Schaakxs et al., 2017). Older people have been shown to more often report somatic symptoms (Hegeman et al., 2012;Miloyan & Pachana, 2016;Schaakxs et al., 2017;Zhao et al., 2018). However, the age-dependent presentation of symptoms is difficult to detect using questionnaire-derived sum scores. While depression sum scores remain consistent across adulthood, older people are more likely to report fatigue, psychomotor agitation, and sleep problems, whereas younger people are more likely to report irritability, concentration problems, and anxiety (Schaakxs et al., 2017). Similarly, endorsement of depression symptoms can vary by sex. Women are more likely to endorse somatic symptoms of fatigue, muscle tension, sleep problems, and appetite problems, whereas men are more likely to endorse suicidal ideation (Fried et al., 2014;Vesga-López et al., 2008). It is unclear whether symptom level age and sex variability extends to GAD symptomology. Given the use of brief measures of generalized anxiety and depression symptoms as the criteria for entry into the UK NHS Improving Access to Psychological Therapies (IAPT) service, it is important to understand how symptom presentations assessed by these measures might vary with age and sex.

| Aims
In the present study, we aim to (a) identify latent factors composed of MDD and GAD symptoms in participants from the Genetic Links to Anxiety and Depression (GLAD) Study and (b) assess how individual MDD and GAD symptoms and our identified factors were associated with age and sex.

| Study design
The GLAD Study is an ongoing study of anxiety and depression (Davies et al., 2019)

| Participants
Our analyses included 35,637 individuals who completed the online questionnaire before May 19, 2020 and had no missing data on age, sex, Generalized Anxiety Disorder (GAD-7), or Patient Health Questionnaire (PHQ-9). Participants reported their biological sex, ethnicity, highest education level, and mental health diagnoses. Age divided by 10 was used in analyses to aid odds ratio (OR) interpretation. Participants' age ranged from 16 to 93 years, with a mean of 38.1 years (SD = 14.4). The majority of the sample was female (79.6%), White (94.3%), and highly educated (Table 1). Overall, 88.2% of participants self-reported an MDD diagnosis and 76.6% a GAD diagnosis.

| Depression and generalized anxiety symptoms
We measured current MDD symptoms with the PHQ-9 (nine items; Kroenke et al., 2001Kroenke et al., , 2010 and current GAD symptoms with the GAD-7 (seven items; Spitzer et al., 2006). These are commonly used self-report scales based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) diagnostic criteria (American Psychiatric Association, 2013). For both scales, individuals rated the frequency of symptoms experienced over the past 2 weeks. Items were rated on a four-point Likert-type scale with scores ranging from 0 (not at all) to 3 (nearly every day). All item scores were summed to create a severity sum score, with values ranging from 0 to 27 for the PHQ-9 and 0 to 21 for the GAD-7. Both scales were psychometrically valid with high test-retest reliability (GAD: r = .83; PHQ: r = .84), and internal consistency (GAD: alpha = .89; PHQ: alpha = .83; Löwe et al., 2008;Spitzer et al., 2006;Thorp et al., 2019).
'EFA was performed in 70% of the sample using the weighted least squares method in the "psych" R package (Revelle, 2017), which is preferred for ordinal data (Forero et al., 2009;Lee et al., 2012). Factors were allowed to correlate using oblimin rotation. The following fit criteria indicated good fit: root mean square error of approximation (RMSEA) ≤ 0.05, Tucker-Lewis Index (TLI) ≥ 0.95, standardized root mean square residuals (SRMR) ≤ 0.05, and a smaller Bayesian Information Criterion (BIC) relative to other models (Hu & Bentler, 1999). Items were retained in a factor for factor loadings of >0.3 and greater than loadings on all other factors. Where multiple models showed adequate fit, the model with factors that encompass the greatest number of items was chosen.
To validate the EFA-derived model, confirmatory factor analysis (CFA) was conducted in the remaining 30% of the sample using the "lavaan" R package (Rosseel, 2012). Standardized fit statistics were interpreted (Hu & Bentler, 1999;Schreiber et al., 2006) and the comparative fit index (CFI) ≥ 0.95 was considered good fit. The CFA was computed in the full sample to provide overview fit statistics.
Two sensitivity analyses were conducted. First, items with a low loading (~0.3) on all factors were sequentially removed. If item removal did not substantially improve model fit, the item was retained.
Second, the final model was computed for males and females separately to assess sex differences in factor structure.

| Age and sex-related variability generalized anxiety and depression
We conducted three sets of regression analyses with age and sex.
First, we fitted linear regressions associating age/10 with PHQ-9 and GAD-7 sum scores while controlling for sex. Each item was transformed into a binary variable to indicate the presence or absence of the symptom; 0 was coded as no symptom, and 1-3 were coded as symptom present. Second, we fitted logistic regressions associating dichotomized symptoms with age per 10 years and sex. Sum scores were also controlled for, to assess only the occurrence of the individual symptom and account for cumulative symptom disorder severity (Schaakxs et al., 2017). For age, an OR > 1 indicated an association with being 10 years older and OR < 1 indicated an association with being 10 years younger. For sex, OR > 1 indicated an association with being female while an OR < 1 indicated an association with being male. Third, we regressed the CFA-derived factor scores on age and sex controlling for disorder severity, to identify symptom groups that may vary across age and between the sexes.
To investigate nonlinear relationships between age and generalized anxiety/depression symptoms, logistic regression models were computed using categorical age. Age was categorized into year groups of 16-23, 24-31, 32-39, 48-55, 56-63, and >64 to avoid a T A B L E 1 Demographic characteristics of the Genetics Links to Anxiety and Depression (GLAD) sample (N = 35,637)   Table 2). The RMSEA was slightly above the recommended threshold (Hu & Bentler, 1999). All other fit statistics indicated good model fit. All factors included two to five items, factor correlations ranged from 0.42 to 0.72 and the four-factor model explained 70% of the variance in the data.
We labeled the four factors according to the loaded items: mood, worry, somatic, and motor symptoms (Figure 1). Factors did not neatly split into GAD and MDD symptoms, for example, motor symptoms contained one symptom from both the PHQ-9 and GAD-7. Five and six-factor models showed slightly better fit; however, these solutions were unsuitable as they included factors with zero items given the loading cut-off of 0.3. See Table S1 for EFA results with all items.
3.1.1 | EFA sensitivity analyses Concentration problems and subsequently irritability (items with the lowest loadings) were dropped from the EFA in an attempt to improve model fit. This solution then showed only a very slight improvement, thus the full model was retained (Table S2). This model was then fitted separately in males and females to check for sex differences in factor loadings. In males, the concentration problems item loaded onto the somatic symptoms factor rather than the mood factor as seen in the full and female only model ( Figure S5).

| CFA
The CFA model is predefined to that identified by EFA, which provides a more stringent test of model fit compared with EFA (Thompson, 2004). The CFA in the remaining 30% of the sample (N = 10,691) confirmed that the four-factor model fit the data well.
The RMSEA (0.068, 95% confidence interval [CI]: 0.067, 0.091) was still slightly above the threshold for good fit (Hu & Bentler, 1999), although lower than that for the EFA. The TLI (0.993), CFI (0.994), and SRMR (0.046) all indicated good fit (Hu & Bentler, 1999 Note: The cut off for each statistic to signify "good" fit is listed in each header (Hu & Bentler, 1999). The model with the lowest BIC is preferred. Cumulative variance is given as an indicator of the variance explained between items by the number of factors in each model. The best fitting and chosen model is indicated in bold.
Abbreviations: BIC, Bayesian information criterion; df, degrees of freedom; RMSEA, root mean square error of approximation; SRMR, standardized root mean square residuals; TLI, Tucker-Lewis fit index.

| Individual symptoms
Eight symptoms were associated with younger age and four with older age, when controlling for sex, generalized anxiety severity and depression severity ( Figure 2a). Irritability and suicide ideation were most strongly associated with younger age, followed by restlessness, weight/appetite problems, motor problems, little energy, feeling anxious, and concentration problems. Sleep change was most strongly associated with older age, followed by difficulty controlling worrying, worrying too much and trouble relaxing. See Table S3 for full OR and CI values.
More symptoms were associated with being male than female ( Figure 2a). Weight/appetite problems, little energy, sleep change, difficulty controlling worrying, and worrying too much were more likely endorsed by females, while suicide ideation, anhedonia, depressed mood, restlessness, worthlessness, concentration problems, and motor problems were more likely endorsed by males. See Table S3 for full OR and CI values.
These associations were replicated using categorical age groups.
Categorical age measurement also identified symptom occurrence that cannot be captured by continuous age. Individuals who were 16-23 or over 64 years were less likely to report concentration problems, little energy, trouble relaxing, weight or appetite problems and worthlessness ( Figure S6). This suggests a nonlinear relationship, where individuals of middle age are more likely to report these symptoms.  Figure 2b). When controlling for age, generalized anxiety severity and depression severity, males were more likely to report mood (β = −.04, p < .001), and motor symptoms (β = −.02, p < .001), while females were more likely to report somatic symptoms (β = .06, p < .001; Figure 2b).

| Latent factors
As expected, the derived factor scores were highly correlated with GAD-7 and PHQ-9 sum scores ( Figure S7). In post hoc sensitivity analyses, regressions were computed without controlling for GAD-7 and PHQ-9 severity sum scores. We observed similar associations for sex, but younger age was associated with all factors ( Figure S8). This is likely due to the over-representation of younger individuals in the GLAD sample; thus, the original model was retained.

| Post hoc sensitivity analyses
Neither excluding participants who had answered either the GAD-7 or the PHQ-9 during the pandemic nor including educational attainment as a covariate led to a substantial change of any of our results as effect sizes across models were highly similar and confidence intervals overlapped (for details, see Tables S4-S12). were also more likely reported by younger men. The worry factor showed no association with age or sex. However, its corresponding symptoms of feeling anxious and irritable were more often reported by younger participants, trouble relaxing by older participants, and difficulty controlling worrying by older women. The somatic factor was associated with being young and female, consistent with its symptoms of little energy and weight/appetite problems. However, sleep change was more likely to be reported by older women. Overall, individual symptoms provide more information on age variation in symptom occurrence, whereas sex variation is apparent across both individual symptoms and factors.
Similar to previous work on generalized anxiety and depressive symptomatology (Ballard et al., 2018;Beard & Björgvinsson, 2014;Clark & Watson, 1991;Kertz et al., 2013), our four-factor model demonstrates that these are not two distinct underlying constructs.
Importantly, we replicated the generalized anxiety and depression factor structure identified in the UK Biobank (Jermy et al., 2020) in a separate, large, and clinically relevant cohort. Thus, our findings demonstrate the need to address the appropriateness of current diagnostic classifications. One difference between our findings and those from the UK Biobank was that they found concentration problems loaded onto the motor factor; we found this for men only. This could suggest two things: First, there are sex differences in the occurrence of concentration problems and the GLAD Study factor representation reflects a more female picture of generalized anxiety and depression.
Second, a cognitive factor of depression and/or generalized anxiety symptomatology may exist that is not captured by the questions comprising both the PHQ-9 and the GAD-7 (LeMoult & Gotlib, 2019).
Our study replicates research that shows variation in depression symptoms across age and sex, that is not captured by sum scores (Fried et al., 2014;Schaakxs et al., 2017), and extends this by providing evidence for similar trends in generalized anxiety symptomatology. Men were more likely to report all motor and mood symptoms. This includes the two main DSM-5 MDD symptoms of depressed mood and anhedonia, which suggests that classic diagnostic criteria reflect presentation most commonly seen in younger men. One contributor could be that men are more likely to have lower perceived social support than women, which has been associated with higher risk of anhedonia, depressed mood, worthlessness, and suicidal ideation (Jokela et al., 2019). In our study, women were F I G U R E 2 Age-and sex-related variation in generalized anxiety and depression in the Genetic Links to Anxiety and Depression (GLAD study; N = 35,637). (a) Odds ratios (OR) and 95% confidence intervals (CI) for the association between all GAD-7 and PHQ-9 items and age (per 10 years) in blue and sex in yellow are shown. (b) Standardized estimates and 95% confidence intervals for the association between four factors of GAD-7 and PHQ-9 symptoms and age (in blue) and sex (in yellow) are shown. For age, points on the right of each panel indicate an association with older age per 10 years and points to the left indicate an association with younger age per 10 years. For sex, points to the right of each panel indicate an association with being female, to the left indicate an association with being male. Filled circle points indicate significant associations while accounting for multiple testing using FDR correction. Transparent circle points indicate nonsignificant associations while accounting for multiple testing using FDR correction. GAD-7, Generalized Anxiety Disorder; FDR, false discovery rate; PHQ-9, Patient Health Questionnaire more likely to report somatic symptoms, consistent with previous findings (Fried et al., 2014). We found that the association between sex and reporting somatic symptoms varied with age, contrary to previous research which found older people were more likely to experience somatic depression symptoms (Hegeman et al., 2012;Schaakxs et al., 2017). Our findings show that older women were more likely to report sleep change and younger women were more likely to report little energy and weight/appetite problems. Sleep problems in older adults could be partly secondary to age-related physical processes (Foley et al., 2004;Smagula et al., 2016), as the circadian system, sleep homeostatic mechanisms, and sleep-related hormone secretion change with advancing age (Li et al., 2018). In our study, age and sex had no association with the worry factor. However, individual symptoms loading on the worry factor differed by age and sex: younger people reported feeling anxious and irritable, whereas older women worried too much and had difficulty controlling their worrying. This replicates findings that older individuals worry about health-related problems (Basevitz et al., 2008;Gonçalves & Byrne, 2013) and worry-related anxiety symptoms could be enhanced by the occurrence of somatic sleep problems in older age (Gould et al., 2016;Lenze et al., 2005). Our findings may have substantial implications for the IAPT service in the United Kingdom that provides psychological treatment for depression and anxiety (Griffiths & Griffiths, 2015). IAPT uses GAD-7 and PHQ-9 sum scores to assess severity and ascertain which patients gain treatment.
Understanding varying age and sex presentations in GAD-7 and PHQ-9 could benefit decision-making around who gains access to treatment.
Some study limitations merit acknowledgment. First, the majority of individuals were White, female, and highly educated. This slightly limits our interpretation of the finding that symptoms vary by sex.
However, our sample size was large and our findings are based on more than 7000 male participants providing sufficient power to detect sex differences. Nevertheless, replication is needed in more ancestrally diverse samples (Bailey et al., 2019). Second, our analyses were cross-sectional and mood symptoms tend to decline over time whereas low levels of somatic symptoms persist (Eeden et al., 2019).
Symptom profiles may vary with age and across the course of the disorder, requiring longitudinal data to better understand this. Third, participants reported severe levels of anxiety and depression (Davies et al., 2019). This could suggest men taking part have more severe symptoms due to the under-detection and under-reporting of milder forms of depression and anxiety by males (Albert, 2015). Fourth, the PHQ-9 and GAD-7 assess a limited range of symptoms; disorder heterogeneity would be better captured by more detailed scales.
However, long questionnaires can lead to participant fatigue and, hence, missing data in large samples, requiring a considered balance  (Schaakxs et al., 2017). Finally, we do not address the multidimensionality in symptom presentations of other anxiety disorders, such as panic disorder and agoraphobia. Although the GAD-7 is considered an adequate screener for all anxiety disorders in theIAPTservice (Beard & Björgvinsson, 2014;Clark, 2011), more research is needed to explore age and sex variation in social anxiety disorder, panic disorder, agoraphobia, social phobia, and specific phobia with more specific questionnaires.
Our study highlights key next steps for generalized anxiety and depression research. Rather than using sum scores, future studies should account for symptom and factor level presentation of gen- lessness that they experience can negatively impact educational attainment and early career goals (Davies et al., 2018). However, our findings were independent of the education level of our participants.
Our findings also provide avenues to better understand anxiety and depression in later life. Many standardized tools including the GAD-7 were designed for measurement in younger individuals (Bryant et al., 2008). Future research that incorporates age-appropriate symptoms would be particularly informative for tracking the longitudinal course of disorders and clinical use in older populations (Lenze et al., 2005).

| CONCLUSION
Our study provides new insights into underlying factors of generalized anxiety and depression symptoms. We identified four factors of mood, worry, somatic, and motor symptoms. Individual symptom and factor endorsement varied significantly dependent on the age and sex of the individual. The current study supports the utilization of individual symptoms or groups of symptoms over the commonly used sum score approach. The results provide possible avenues for diagnostic improvement and treatment intervention by accounting for age-and sex-related variation in symptoms of generalized anxiety and depression.
Ian R. Jones