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research-article2014
ASMXXX10.1177/1073191114544357AssessmentWilliamson et al.
Article
Assessment of Postpartum Depressive Symptoms: The Importance of Somatic Symptoms and Irritability
Assessment 2015, Vol. 22(3) 309–318 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1073191114544357 asm.sagepub.com
J Austin Williamson1, Michael W. O’Hara1, Scott Stuart1, Kimberly J. Hart2, and David Watson3
Abstract Assessing postpartum depressive symptoms is complicated by the fact that irritability, fatigue, insomnia, and appetite disruptions are also related to normative aspects of the childbearing process. We used multigroup confirmatory factor analysis to compare symptoms in 271 postpartum women with those of 820 non-postpartum women. We found that (a) irritability, insomnia, fatigue, and appetite loss were substantially associated with depressed mood among postpartum women whereas increased appetite was not; (b) irritability, insomnia, fatigue, and appetite changes were as strongly related to depression among postpartum women as they were among non-postpartum women; and (c) after controlling for overall depressed mood, postpartum women reported more irritability, insomnia, and appetite loss than the non-postpartum women. Irritability, fatigue, insomnia, and appetite loss are valid indicators and should be used to measure postpartum depressive symptoms. However, scores on these symptoms should be adjusted downward to account for their higher baseline rates in the postpartum population. Keywords postpartum depression, screening, sleep, fatigue, appetite, irritability Approximately 19% of mothers will experience clinically significant depressive symptoms during the first 3 months after giving birth (Gavin et al., 2005). Not only do these women experience considerable emotional distress, but depressed mothers are often less responsive to their infants (Flykt, Kanninen, Sinkkonen, & Punamäki, 2010) and less likely to engage in recommended infant-health practices (Zajicek-Farber, 2009). Accurate assessment of depressive symptoms during the postpartum period is essential, both to identify women for treatment and for conducting research on the risk factors, protective factors, and effective interventions for postpartum depression. However, assessing depressive symptoms during the postpartum period is complicated by the fact that pregnancy, childbirth, and breastfeeding sometimes induce several of the symptoms used to identify depression. Many women experience disruptive changes in appetite, sleep, and energy after having a baby (Glazener et al., 1995); and irritability, another correlate of depressed mood, also is more common during the postpartum period (Bowen, Bowen, Balbuena, & Muhajarine, 2012). To the extent that somatic disruptions and irritability are caused by physiological changes associated with pregnancy, childbirth, breastfeeding, or altered sleep schedules due to child care, using these symptoms as indicators of depression may lead clinicians or researchers to overestimate depression
severity in postpartum women. If these symptoms are not indicative of mood disturbance among the postpartum population, screening tools that include them will be less precise and more likely to misidentify women for treatment. Moreover, research instruments that include poor indicators of depression will be less valid, less internally consistent, and therefore show weaker associations with other constructs (Schmidt, Le, & Ilies, 2003). Conversely, if physicians incorrectly assume that new mothers’ somatic symptoms or irritability are an inevitable consequence of childbirth, they may miss important signs of postpartum depression. Researchers who use instruments without valuable indicators of depression will obtain biased findings and potentially draw misleading conclusions because of incomplete coverage of the depression construct. In fact, many women are more aware of and/or more willing to report their somatic symptoms than their low mood 1
University of Iowa, Iowa City, IA, USA University of Illinois College of Medicine at Rockford, IL, USA 3 University of Notre Dame, Notre Dame, IN, USA 2
Corresponding Author: J Austin Williamson, Department of Psychology, University of Iowa, 11 Seashore Hall E, Iowa City, IA 52242, USA. Email: [email protected]
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(Simon, VonKorff, Piccinelli, Fullerton, & Ormel, 1999). These symptoms, therefore, would be particularly important indicators of depression if they are indeed likely to signal a mood disturbance.
Somatic Disruptions Following Childbirth Several features of the postpartum period are likely to cause the same somatic symptoms that sometimes accompany depressed mood. The disruptions to maternal sleeping schedules caused by nighttime feedings often make sleeping difficult even when the infant allows the mother to sleep (Lee, Zaffke, & McEnany, 2000). Consequently, about half of new mothers report significant insomnia (Ko et al., 2012). Sleep loss often leads to fatigue during the postpartum period (Rychnovsky & Hunter, 2009), as do reduced levels of ferritin and hemoglobin (Lee & Zaffke, 1999), which can result from pregnancy and/or childbirth (Milman, 2011). An estimated 42% to 59% of postpartum women experience substantial fatigue (Glazener et al., 1995; Lee & Zaffke, 1999). Changes in appetite vary. Women who breastfeed need, on average, an additional 670 calories per day (Dewey, 1997) and experience a concomitant increase in appetite. Women who do not breastfeed, or who stop doing so, will begin to need fewer calories, but the speed with which mothers’ eating patterns converge with their reduced caloric needs is quite variable (Lipsky, Strawderman, & Olson, 2012). All these factors can create uncertainty as to whether changes in energy level, appetite, and the ability to fall /stay asleep are likely to be indicative of depressed mood.
Irritability Following Childbirth Increased anger and irritability also are common features of the postpartum period. In fact, postpartum women are more likely to experience elevations in irritable mood than elevations in depressed or anxious mood (Bowen et al., 2012). Similar to fatigue, irritability during the postpartum period may be because of disrupted sleeping schedules (Kamphuis, Meerlo, Koolhaas, & Lancel, 2012), but it also may also be related to broader mood disturbance. Irritability and depression are strongly correlated in general populations and irritability commonly accompanies major depressive disorder (Fava et al., 2010). The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) does not include irritability as a criterion for major depressive disorder for adults but references to irritable mood appear frequently in the DSM’s qualitative description of that disorder.
Indicators of Postpartum Depression The present study was undertaken to address three questions pertaining to the validity of irritability, fatigue, insomnia, and appetite changes as indicators of depression in the
postpartum: (1) Do these symptoms show strong enough associations with depressed mood to constitute valuable indicators of depression? (2) Are the associations between these symptoms and depressed mood similar for postpartum women and non-postpartum women? (3) After accounting for depressed mood, do postpartum women experience higher rates of these symptoms than non-postpartum women? Question 1. Table 1 summarizes previously conducted studies bearing on Question 1. These studies have used a variety of depression measures and a variety of data analytic strategies. Cumulatively, they show that fatigue is consistently associated with depressed mood, as is irritability when irritability is assessed. The findings for changes in sleep and appetite are not uniform, though insomnia is generally correlated with depressed mood. Apparent from Table 1 is the fact that the majority of these instruments do not assess all four of the symptoms under our consideration. For instance, the Edinburgh Postnatal Depression Scale (EPDS; Cox, Holden, & Sagovsky, 1987), a commonly used measure for screening and research on postpartum depression, does not contain items for fatigue, appetite, or irritability. The EPDS was designed under the assumption that these symptoms could not be used to discriminate depressed from nondepressed women in the postpartum period. Should this assumption be incorrect, the EPDS and other instruments missing these symptoms would be less valid for having omitted them. In addition to inconsistent symptom coverage, the heterogeneity of the findings in Table 1 may be partly explained by unreliable measurement. With the exception of Beck and Gable (2001), the assessment instruments used in these studies use only one item to measure each depression symptom, a practice that is not optimal for establishing high reliability of measurement. In the research we describe here, we used the Inventory of Depression and Anxiety Symptoms (IDAS; Watson et al., 2007), which measures depressive symptoms with multi-item scales. Each of these scales has demonstrated high internal consistency and short-term retest reliability (Watson et al., 2007). Question 2. With the exception of Bernstein et al. (2008), the studies in Table 1 do not compare postpartum and non-postpartum women. This comparison is important because it allows us to determine whether indicators that perform poorly in the postpartum period do so because of something unique to that period or because they are generally weak markers of depressed mood. The item response theory analysis by Bernstein et al. (2008) was informative in this respect. They found that low energy and disrupted sleep showed associations of similar magnitude with underlying depression in their postpartum and non-postpartum groups, whereas the association between appetite changes and depression was significantly weaker among postpartum women.
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Williamson et al. Table 1. Are Insomnia, Fatigue, Appetite Changes, and Irritability Indicative of Postpartum Depression? Study Beck and Gable (2001)
Bernstein et al. (2008)
Bernstein et al. (2008)
Carvalho Bos et al. (2009) Kammerer et al. (2009)
Ross, Gilbert Evans, Sellers, and Romach (2003a) Ross, Gilbert Evans, Sellers, and Romach (2003b) Sugawara, Sakamoto, Kitamura, Toda, and Shima (1999)
Sample
Instrument
150 Postpartum women (46 with a diagnosis of major or minor depression) 95 Postpartum depressed women and 50 nonpostpartum depressed women 95 Postpartum depressed women and 50 nonpostpartum depressed women 354 Postpartum women
Postpartum Depression Screening Scale
16-Item Quick Inventory of Depressive Symptomatology–SelfReport 16-Item Quick Inventory of Depressive Symptomatology–SelfReport Beck Depression Inventory–II Structured Clinical Interview for DSM-IV
38 Postpartum depressed women and 606 postpartum nondepressed women 150 Postpartum women
150 Postpartum women
Edinburgh Postnatal Depression Scale Hamilton Rating Scale for Depression
1,002 Postpartum women Zung Self-Rating Depression Scale
Analysis
Insomnia
Fatigue
Appetite
Irritability
Significant correlation with depression diagnosis
Yes
N/A
Yes
Yes
Item–total correlations above .30
No
Yes
No
N/A
Item response theory (equivalent slopes in postpartum/nonpostpartum groups) Factor analysis (loadings above .40) Chi-square (do symptoms differentiate depressed vs. nondepressed) Principal component analysis (loadings above .40) Item–total correlations above .30
Yes
Yes
No
N/A
Yes
Yes
Yes
Yes
Yes
Yes
No
N/A
Yes
N/A
N/A
N/A
Yes
Yes
Yes
N/A
Yes
Yes
No
Yes
Item–total correlations above .30
Note. This table summarizes studies that bear on the validity of insomnia, fatigue, appetite disturbance, and irritability as indicators of depressed mood during the postpartum period. The last four columns indicate whether, based on the analysis and criteria described in column 4, a given indicator was found to be sufficiently associated with overall depression to be considered a valuable indicator. N/A indicates that the instrument used in a given study did not include a measure of the given construct.
Bernstein et al. (2008) did not measure irritability and their analysis focused on the statistical significance of the differences between the two groups rather than the substantive magnitude of those differences. We report effect sizes recently developed by Nye and Drasgow (2011) that identify those differences that are meaningful versus those that are insubstantial despite being statistically significant. These effect sizes are generated through multigroup confirmatory factor analysis (MG-CFA). MG-CFA and the IRT analyses used by Bernstein et al. (2008) yield similar information but MG-CFA is the appropriate framework for the present study because our indicators are scale scores rather than the item scores analyzed by Bernstein et al. (2008).
represent the expected value of an observed indicator at a given level of the latent factor. The MG-CFA analyses we use identify group differences in the average level of an observed indicator (in this case, a symptom) that cannot be accounted for by any group differences in the latent factor (overall depressed mood). Only Bernstein et al. (2008) have addressed intercepts. They found that when holding depression constant, postpartum women reported significantly more trouble sleeping than non-postpartum controls; the intercepts for appetite and energy were equivalent across groups. We build on Bernstein et al.’s (2008) analysis by using multi-item scales, calculating effect sizes, and adding a measure of irritability.
Question 3. We emphasize that Questions 1 and 3 are distinct. Irritability, fatigue, insomnia, and disturbed appetite may be more prevalent among the postpartum population (Question 3) and still be correlated with depressed mood (Question 1). Alternatively, we may observe similar rates of these symptoms between the two groups (Question 3) but find that the symptoms are not related to mood disturbance among postpartum women (Question 1). Question 3 cannot be resolved through the examination of item–total correlations or factor loadings but pertains instead to the intercepts of each indicator. Similar to regression, intercepts in CFA
Hypotheses Based on the findings outlined above, we expected to find that insomnia, fatigue, and irritability would be valid indicators of depressed mood during the postpartum period and would be related to it at least as strongly as in the general population of women. Because previous studies have yielded inconsistent findings regarding the validity of appetite disturbance as an indicator of depressed mood during the postpartum period, the degree to which appetite changes would be associated with depressed mood was treated as an
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Table 2. Depressive Symptoms Scales: Means, Standard Deviations, and Intercorrelations. Scale 1. Dysphoria 2. rWell-Being 3. Ill Temper 4. Lassitude 5. Insomnia 6. Appetite Loss 7. Appetite Gain 8. Suicidality
Postpartum, n = 271, mean (SD)
Non-postpartum, n = 820, mean (SD)
1
17.78 (7.51) 16.85 (6.64) 9.07 (4.27) 12.08 (4.84) 12.66 (5.74) 5.26 (2.88) 5.83 (3.08) 6.67 (1.74)
19.98 (7.86) 16.51 (6.82) 8.04 (3.64) 13.07 (5.21) 11.36 (4.88) 4.67 (2.32) 6.53 (3.06) 7.06 (2.29)
.47 .71 .71 .61 .40 .32 .52
2
3
.51 .64 .33 .40 .31 .53 .30 .51 .20 .27 .09 .24 .19 .40
4
5
6
7
.72 .52 .48 .42 .38 .24 .22 .15 .48 .43 .33 .36 .45 .36 .45 .52 .40 .25 .28 .40 .06 .38 .27 .21 .39 .22 .19 .11
8 .58 .36 .49 .44 .30 .24 .32
Note. Well-Being was reverse scored. Correlations below the diagonal are from the postpartum group, correlations above the diagonal are from the non-postpartum group. Bolded correlations are statistically significant at p < .05.
open question. We further anticipated that the baseline severity of all four symptoms would be higher among postpartum women, evidenced by higher intercepts for the corresponding indicators.
Method Participants and Procedures The 271 women in our postpartum sample were recruited through infant birth records from the state of Iowa and at maternal and child health centers in Iowa and Michigan. These women took part in a study that was originally aimed at developing a brief scale to detect postpartum depression (O’Hara et al., 2012). Mailed questionnaires were returned by 1,077 participants, and we selected all those completed within 12 weeks of the target child’s birth. A cutoff of 12 weeks postpartum was chosen in order to restrict our sample to women whose depressive symptoms were most likely to be affected by their recent childbirth while adhering to the recommendation by Meade, Johnson, and Braddy (2008) that each group included in multigroup analyses should exceed 200 observations. On average, these women were 27.9 years old (SD = 5.3) and 7.1 weeks postpartum (SD = 3.4). The vast majority were White (97%). Our non-postpartum sample was 820 women of childbearing age (defined as 18-45 years old) recruited in Iowa and Indiana as part of several studies on the factor structure of internalizing psychopathology (McDade-Montez & Watson, 2011; Watson et al., 2007; Watson et al., 2008; Watson et al., 2012). Their average age was 29.5 (SD = 7.8) and 88% of the women were White.
Measures Participants completed the eight depression scales of the IDAS (Watson et al., 2007). The IDAS scales were developed through factor analysis across many large samples, so that the composition of these scales reflects the factor structure of depression as observed from these analyses. Symptoms from
the preceding 2 weeks are measured on a 5-point scale from Not at all to Extremely. The Dysphoria scale (10 items) measures low mood, feelings of worthlessness, concentration problems, guilt, difficulty making decisions, and psychomotor disturbances. Although the composition of the Dysphoria scale may appear somewhat heterogeneous, these items consistently define a single, internally consistent latent factor (Watson et al., 2007). The Well-Being scale (8 items) assesses current levels of positive mood and satisfaction with life. The Ill Temper scale (5 items) measures irritability and anger. The Lassitude scale (6 items) measures low energy and hypersomnia. The Insomnia scale (6 items) measures difficulty falling and staying asleep. The Appetite Loss (3 items) and Appetite Gain (3 items) scales measure unusually low and high appetite, respectively. The Suicidality scale (6 items) measures self-harm and thoughts of suicide. All the IDAS scales have demonstrated good convergent validity with interviewer-rated measures of the same symptoms (Watson et al., 2007; Watson et al., 2008). They also showed good internal consistency in the community (αs = .77-.90) and postpartum samples (αs = .76-.89) used in the present analysis.
Analysis and Results The means, standard deviations, and intercorrelations for the eight IDAS depressive symptom scales in both groups are presented in Table 2. The community sample was missing data from 0.2% of the item responses and the postpartum sample was missing data from 0.1%. Prior to analysis, missing data were imputed using PROC MI in SAS version 9.2 (SAS Institute, Inc., Raleigh, NC). We used factor analysis to determine whether the eight depressive symptoms function as valid indicators of depression during the postpartum period. The construct of depression was conceptualized as a latent factor comprising the common variance among the eight symptoms. Factor analysis was conducted in Mplus 6.11 (Muthén & Muthén, 2010). Because our indicators were continuous variables with right-skewed distributions, we used maximum likelihood estimation with robust standard errors (the MLR estimator). The Well-Being
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Williamson et al. scale was reverse scored such that higher scores reflected lower levels of well-being. In accordance with Hu and Bentler (1999), we interpreted root mean square error of approximation (RMSEA) close to or below .06 and comparative fit index (CFI) close to or above .95 to indicate a good model fit. Scales with standardized factor loadings above .40 were interpreted as valuable indicators of depression (Clark & Watson, 1995). We then used a measurement invariance framework to compare the factor structure of depression in the postpartum and non-postpartum samples. Because our hypotheses pertained to the differential functioning of individual indicators rather than establishing the invariance of the IDAS as a whole, we used the free-baseline approach advocated by Stark, Chernyshenko, and Drasgow (2006). For the baseline model, we constrained the parameters of one referent indicator to equality while the parameters of the other seven indicators were free to vary between groups. The baseline model was then compared with seven constrained models in which a single parameter of one of the indicators was constrained to equality. Because our hypotheses concerned substantive differences between the postpartum and non-postpartum groups with respect to both factor loadings and intercepts, we tested for invariance in loadings and intercepts separately (Church et al., 2011). Although our hypotheses pertained only to the Ill Temper, Insomnia, Lassitude, Appetite Loss, and Appetite Gain scales, we examined the between-group differences for the parameters of all eight IDAS scales. We computed the difference in the CFI between the baseline and constrained models to evaluate invariance in each parameter. Chen (2007) has suggested that a difference of greater than or equal to .005 indicates a lack of invariance when the sample sizes of the two groups are not equal. Effect sizes representing the magnitude of nonequivalence between indicators were calculated using the dMACS computer program (Nye & Drasgow, 2011). We interpreted effect sizes using Cohen’s (1988) guidelines—effects below 0.2 are insubstantial, effects 0.2 to 0.5 are small, effects 0.5 to 0.8 are moderate, and effects above 0.8 are large.
Question 1: Indicators of Depressed Mood During the Postpartum We first used CFA to determine the strength of the associations between each depressive symptom and the latent construct of depressed mood. In CFA, these associations are represented by the factor loadings of an observed variable on an unobserved, or latent, variable that represents the common variance shared by all the observed variables. Previous factor analyses of the IDAS depression scales have demonstrated that a single latent factor accounts for the covariance between the scales, provided that the residuals of the Appetite Loss and Appetite Gain scales are
allowed to correlate (Nylen, Williamson, O’Hara, Watson, & Engeldinger, 2013). This model showed a good fit (RMSEA = .063, CFI = .964) in the postpartum sample. As Figure 1 shows, all the standardized factor loadings for the postpartum group were above .40 with the exception of Appetite Gain (λ = .35).
Question 2: Equivalence of Factor Loadings Before attempting to determine whether the factor loadings in the postpartum group were equivalent in magnitude to those in the non-postpartum group, we first needed to demonstrate that the factor structures in each group showed the same configuration. A factor structure demonstrates configural invariance across groups when that structure is composed of the same number of factors in each group and each of those factors is defined by the same indicators (Meredith, 1993). We tested the model that fit the postpartum sample using MG-CFA, allowing seven of the eight factor loadings and intercepts to vary between the groups. As recommended by Steenkamp and Baumgartner (1998), we constrained the factor loading and intercept of a referent indicator and fixed the mean of the non-postpartum group at zero to identify the model. The referent indicator was chosen based on a factorratio test (Cheung & Rensvold, 1999) in which the fit of 28 models comprising every possible combination of two indicators with constrained parameters (loadings and intercepts) was compared with the fit of a model in which only one indicator’s parameters were constrained. From the invariant set of indicators identified by the factor-ratio test, Dysphoria was chosen as a referent indicator because its standardized loading was most similar across the two groups when that parameter was allowed to vary. The configural model, presented in Figure 1, showed an adequate fit (RMSEA = .066, CFI = .959), suggesting that the broad structure of depressive symptoms is not different during the postpartum period. With configural invariance established, we then tested for metric invariance, which pertains to the equivalence of factor loadings across groups. Table 3 presents the parameters for the configural model with the change in CFI resulting from the constraint of each factor loading. As Table 3 shows, each constraint resulted in a ΔCFI of less than .005, meaning that we did not identify a lack of invariance for any of the loadings. The metric invariance model with all eight factor loadings constrained to equality across groups showed an adequate fit to the data (RMSEA = .066, CFI = .953).
Question 3: Equivalence of Intercepts Scalar invariance pertains to the equivalence of indicator intercepts across groups. In the baseline model for testing the scalar invariance of each indicator, all eight factor loadings were constrained to equality across groups, as was the
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Postpartum Depression
.95
Dysphoria
Well-Being
.48
.74
Ill Temper
.75
.65
Lassitude
Insomnia
.42
.35
Appe te Loss
.52
Appe te Gain
Suicidality
-.41
Non-postpartum Depression
.94
Dysphoria
Well-Being
.52
.69
Ill Temper
.76
.57
Lassitude
Insomnia
.50
.47
Appe te Loss
.61
Appe te Gain
Suicidality
-.38
Figure 1. Standardized factor loadings for the configural model.
Note. Well-Being is reverse scored. All coefficients are statistically significant.
Table 3. Indicator Parameter Discrepancies Between the Postpartum and Non-Postpartum Groups. Factor loading (λi) Scale Dysphoria rWell-Being Ill Temper Lassitude Insomnia Appetite Loss Appetite Gain Suicidality
Intercept (τi)
Postpartum
Non-postpartum
ΔCFI
Postpartum
Non-postpartum
ΔCFI
dMACS
−1.00 0.45 −0.44 −0.51 −0.52 −0.17 −0.15 −0.13
−1.00 0.48 −0.34 −0.54 −0.37 −0.16 −0.20 −0.19
— .000 .003 .000 .003 .000 .000 .001
19.98 22.16 10.04 13.20 13.81 5.64 6.16 7.00
19.98 23.49 8.04 13.07 11.36 4.67 6.53 7.06
— .004 .021 .001 .014 .009 .001 .000
— 0.09 0.37 0.01 0.36 0.23 0.12 0.14
Note. Well-Being was reverse scored. All parameters are unstandardized. Bolded parameters differed significantly (ΔCFI ≥ .005) across groups.
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Williamson et al. intercept for dysphoria. The intercepts were then tested for lack of invariance one by one in the same manner as the factor loadings. Table 3 shows the unconstrained intercepts from the configural model along with the change in CFI corresponding to the invariance test for each of them. These tests showed that the intercepts for three indicators were significantly different (ΔCFI ≥ .005) between the groups: The intercepts for Ill Temper, Insomnia, and Appetite Loss were all higher in the postpartum group. The partial scalar invariance model with these three intercepts freed showed an adequate fit (RMSEA = .066, CFI = .949). Finally, we input the unstandardized parameters from the configural invariance model into the dMACS computer program to ascertain the magnitude of invariance in the indicators. The generated effect sizes take into account invariance in both loadings and intercepts. We observed small differences between the groups for the Ill Temper, Insomnia, and Appetite Loss scales; the differences for the other five scales were insubstantial (Table 3). The dMACS program also identifies the impact of the cumulative lack of invariance for all parameters on the difference between the means of the latent variables. Our analyses showed that the mean of the latent depression score was 33.63 (SD = 19.32) in the postpartum group and 27.24 (SD = 19.06) in the non-postpartum group but that noninvariance in the indicators lead to an overestimation of the postpartum mean by 1.95. The difference between the sum of the IDAS depression scales for postpartum women and the sum of the IDAS depression scales for non-postpartum women does not accurately reflect the difference in depressed mood between postpartum and non-postpartum women. The sum of the IDAS depression scales for postpartum women is inflated by an average of 1.95 points because of elevations in Ill Temper, Insomnia, and Appetite Loss during the postpartum period that are not related to depressed mood.
Discussion Summary and Interpretation of Results Based on conventional standards, all the IDAS depression scales were valuable indicators of depressed mood during the postpartum period with the exception of appetite gain, which showed an equivocal loading on the latent depression factor. However, the loading for appetite gain in the postpartum sample was not significantly different from that of the non-postpartum sample. This finding is consistent with other studies of depression in the general population that suggest that increases in appetite and weight are ambiguous criteria for major depressive disorder (McGlinchey, Zimmerman, Young, & Chelminski, 2006). We found no significant differences between the postpartum and non-postpartum groups in the degree to which
any of the symptoms of interest were related to depression. Similar to Bernstein et al. (2008), we found that postpartum women reported higher baseline levels of insomnia. Unlike Bernstein et al. (2008), we observed that postpartum women also reported higher baseline levels of appetite loss, and irritability. Controlling for level of depressed mood, the severity of fatigue and appetite gain were equivalent across the groups.
Implications of the Findings Our findings do not support the use of increased appetite as an indicator of depression during the postpartum period but do support the inclusion of indicators for insomnia, fatigue, decreased appetite, and irritability. These results are particularly notable given that many of the instruments used to screen and assess postpartum depressive symptoms, including the popular EPDS, do not include such indicators. The results also reinforce calls by other investigators to include questions about irritability as part of any comprehensive depression assessment (Fava et al., 2010). We note that irritability during the postpartum period appears to abate in response to the same cognitive behavioral interventions that are effective for depression (Marrs, 2013). The higher intercepts for insomnia, appetite loss, and irritability indicate that a given level of one of these symptoms would not suggest the same level of depressed mood in postpartum women as it would for women in the general population. For example, a postpartum woman who scored a 15 on the IDAS Insomnia scale is likely to be experiencing less depressed mood than a non-postpartum woman with an Insomnia score of 15. A score of 15 on the IDAS Insomnia scale for a postpartum woman would indicate about the same level of depressed mood as a score of 13 for a non-postpartum woman. In the same way, it is likely that a postpartum woman’s score of 2 on the sleep disturbance item of the Patient Health Questionnaire-9 (Kroenke, Spitzer, & Williams, 2001) is not equivalent to a non-postpartum woman’s score of 2. In sum, questions about irritability, insomnia, and loss of appetite should be included in any assessment of postpartum depression, but higher scoring thresholds for these items may lead to more valid overall scores when doing screening and research. With large, representative samples, both MG-CFA and item response theory analyses can be used to norm screening and research instruments and create simple scoring algorithms that take into account the expected elevations in these symptoms.
Strengths and Limitations Our investigation benefitted from sample sizes that were larger than most of the previous studies on this topic. Rather than using potentially unreliable single-item indicators for
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our constructs of interest, we used multi-item scales with established retest reliability and good internal consistency in the present samples. Additionally, our instrument was more comprehensive than others used by previous researchers and we calculated effect sizes for interpreting the magnitude of the differences between our postpartum and non-postpartum groups. With respect to the study’s limitations, we emphasize the correlational nature of these findings. For instance, based on the substantial factor loading for insomnia on depression, we cannot determine the extent to which depressed mood causes insomnia or the extent to which lack of sleep causes depressed mood. Interestingly, cognitive behavioral treatment of postpartum insomnia has been shown to alleviate depressive symptoms (Swanson, Flynn, Adams-Mundy, Armitage, & Arnedt, 2013). We also note that depressive symptoms were measured exclusively through self-report, and the associations between these symptoms likely were inflated by common method variance. Additionally, our two samples contained limited diversity. It is unlikely that more diverse samples would yield substantively different results, however, given that the characteristics of depression indicators under our analysis appear to be generally invariant across demographic groups (Golding & Aneshensel, 1989; Gregorich, 2006). Finally, the IDAS is strongly related to clinical impairment (Watson et al., 2008), but investigators have yet to clarify the range of IDAS scores that suggest treatment for depression is warranted. Therefore, although we can say, in relative terms, that insomnia (along with irritability and appetite loss) must be more severe in postpartum women for it to indicate depressed mood, we cannot say how severe insomnia must be, in absolute terms, before it is likely to indicate a mood disturbance that demands clinical intervention.
Conclusion A comprehensive assessment of depressive symptoms during the postpartum period should include questions about insomnia, fatigue, loss of appetite, and irritability. Insomnia, appetite loss, and irritability indicate depressed mood only at higher levels than outside the perinatal period. Future research is needed to establish the severity of depressive symptoms that identify postpartum women who are in need of psychological treatment. Acknowledgments We thank Lisa Segre and Jennifer McCabe for their help in the preparation of this article.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Support for this research was provided by the Centers for Disease Control and Prevention (MM-0822, S. Stuart, PI) and by the National Institute of Mental Health (MH068472, D. Watson, PI).
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Reproductive and Infant Psychology, 31, 72-80. doi:10.1080/ 02646838.2012.747676 McDade-Montez, E. A., & Watson, D. (2011). Examining the potential influence of diabetes on depression and anxiety symptoms via multiple sample confirmatory factor analysis. Annals of Behavioral Medicine, 42, 341-351. doi:10.1007/ s12160-011-9298-5 McGlinchey, J. B., Zimmerman, M., Young, D., & Chelminski, I. (2006). Diagnosing major depressive disorder VIII: Are some symptoms better than others? Journal of Nervous and Mental Disease, 194, 785-790. doi:10.1097/01. nmd.0000240222.75201.aa Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in test of measurement invariance. Journal of Applied Psychology, 93, 568-592. doi:10.1037/0021-9010.93.3.568 Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525-543. doi:10.1007/BF02294825 Milman, N. (2011). Postpartum anemia I: Definition, prevalence, causes, and consequences. Annals of Hematology, 90, 1247-1253. doi:10.1007/s00277-011-1279-z Muthén, L. K., & Muthén, B. O. ( 2010 ) Mplus 6.1. [Statistical software] Los Angeles, CA : Muthén & Muthén Nye, C. D., & Drasgow, F. (2011). Effect size indices for analyses of measurement equivalence: Understanding the practical importance of differences between groups. Journal of Applied Psychology, 96, 966-980. doi:10.1037/a0022955 Nylen, K., Williamson, J. A., O’Hara, M. W., Watson, D., & Engeldinger, J. (2013). Validity of somatic symptoms as indicators of depression in pregnancy. Archives of Women’s Mental Health, 16, 203-210. doi:10.1007/s00737-0130334-2 O’Hara, M. W., Stuart, S., Watson, D., Dietz, P. M., Farr, S. L., & D’Angelo, D. (2012). Brief scales to detect postpartum depression and anxiety symptoms. Journal of Women’s Health, 21, 1237-1243. doi:10.1089/jwh.2012.3612 Ross, L. E., Gilbert Evans, S. E., Sellers, E. M., & Romach, M. K. (2003a). Measurement issues in postpartum depression part 1: Anxiety as a feature of postpartum depression. Archives of Women’s Mental Health, 6, 51-57. doi:10.1007/s00737-0020155-1 Ross, L. E., Gilbert Evans, S. E., Sellers, E. M., & Romach, M. K. (2003b). Measurement issues in postpartum depression part 2: Assessment of somatic symptoms using the Hamilton Rating Scale for Depression. Archives of Women’s Mental Health, 6, 59-64. doi:10.1007/s00737-002-0156-0 Rychnovsky, J., & Hunter, L. P. (2009). The relationship between sleep characteristics and fatigue in healthy postpartum women. Women’s Health Issues, 19, 38-44. doi:10.1016/j. whi.2008.07.015 Schmidt, F. L., Le, H., & Ilies, R. (2003). Beyond alpha: An empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs. Psychological Methods, 8, 206-224. doi:10.1037/1082-989X.8.2.206 Simon, G. E., VonKorff, M., Piccinelli, M., Fullerton, C., & Ormel, J. (1999). An international study of the relation between somatic symptoms and depression. New
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Watson, D., O’Hara, M. W., Chmielewski, M., McDade-Montez, E. A., Koffel, E., Naragon, K., & Stuart, S. (2008). Further validation of the IDAS: Evidence of convergent, discriminant, criterion, and incremental validity. Psychological Assessment, 20, 248-259. doi:10.1037/a0012570 Watson, D., O’Hara, M. W., Naragon-Gainey, K., Koffel, E., Chmielewski, M., Kotov, R., . . .Ruggero, C. J. (2012). Development and validation of new anxiety and bipolar symptom scales for an expanded version of the IDAS (the IDAS-II). Assessment, 19, 399-420. doi:10.1177/1073191112449857 Watson, D., O’Hara, M. W., Simms, L., Kotov, R., Chmielewski, M., McDade-Montez, E., . . .Stuart, S. (2007). Development and validation of the inventory of depression and anxiety symptoms (IDAS). Psychological Assessment, 19, 253-268. doi:10.1037/1040-3590.19.3.253 Zajicek-Farber, M. L. (2009). Postnatal depression and infant health practices among high-risk women. Journal of Child and Family Studies, 18, 236-245. doi:10.1007/s10826-0089224-z
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research-article2014
ASMXXX10.1177/1073191114544357AssessmentWilliamson et al.
Article
Assessment of Postpartum Depressive Symptoms: The Importance of Somatic Symptoms and Irritability
Assessment 2015, Vol. 22(3) 309–318 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1073191114544357 asm.sagepub.com
J Austin Williamson1, Michael W. O’Hara1, Scott Stuart1, Kimberly J. Hart2, and David Watson3
Abstract Assessing postpartum depressive symptoms is complicated by the fact that irritability, fatigue, insomnia, and appetite disruptions are also related to normative aspects of the childbearing process. We used multigroup confirmatory factor analysis to compare symptoms in 271 postpartum women with those of 820 non-postpartum women. We found that (a) irritability, insomnia, fatigue, and appetite loss were substantially associated with depressed mood among postpartum women whereas increased appetite was not; (b) irritability, insomnia, fatigue, and appetite changes were as strongly related to depression among postpartum women as they were among non-postpartum women; and (c) after controlling for overall depressed mood, postpartum women reported more irritability, insomnia, and appetite loss than the non-postpartum women. Irritability, fatigue, insomnia, and appetite loss are valid indicators and should be used to measure postpartum depressive symptoms. However, scores on these symptoms should be adjusted downward to account for their higher baseline rates in the postpartum population. Keywords postpartum depression, screening, sleep, fatigue, appetite, irritability Approximately 19% of mothers will experience clinically significant depressive symptoms during the first 3 months after giving birth (Gavin et al., 2005). Not only do these women experience considerable emotional distress, but depressed mothers are often less responsive to their infants (Flykt, Kanninen, Sinkkonen, & Punamäki, 2010) and less likely to engage in recommended infant-health practices (Zajicek-Farber, 2009). Accurate assessment of depressive symptoms during the postpartum period is essential, both to identify women for treatment and for conducting research on the risk factors, protective factors, and effective interventions for postpartum depression. However, assessing depressive symptoms during the postpartum period is complicated by the fact that pregnancy, childbirth, and breastfeeding sometimes induce several of the symptoms used to identify depression. Many women experience disruptive changes in appetite, sleep, and energy after having a baby (Glazener et al., 1995); and irritability, another correlate of depressed mood, also is more common during the postpartum period (Bowen, Bowen, Balbuena, & Muhajarine, 2012). To the extent that somatic disruptions and irritability are caused by physiological changes associated with pregnancy, childbirth, breastfeeding, or altered sleep schedules due to child care, using these symptoms as indicators of depression may lead clinicians or researchers to overestimate depression
severity in postpartum women. If these symptoms are not indicative of mood disturbance among the postpartum population, screening tools that include them will be less precise and more likely to misidentify women for treatment. Moreover, research instruments that include poor indicators of depression will be less valid, less internally consistent, and therefore show weaker associations with other constructs (Schmidt, Le, & Ilies, 2003). Conversely, if physicians incorrectly assume that new mothers’ somatic symptoms or irritability are an inevitable consequence of childbirth, they may miss important signs of postpartum depression. Researchers who use instruments without valuable indicators of depression will obtain biased findings and potentially draw misleading conclusions because of incomplete coverage of the depression construct. In fact, many women are more aware of and/or more willing to report their somatic symptoms than their low mood 1
University of Iowa, Iowa City, IA, USA University of Illinois College of Medicine at Rockford, IL, USA 3 University of Notre Dame, Notre Dame, IN, USA 2
Corresponding Author: J Austin Williamson, Department of Psychology, University of Iowa, 11 Seashore Hall E, Iowa City, IA 52242, USA. Email: [email protected]
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(Simon, VonKorff, Piccinelli, Fullerton, & Ormel, 1999). These symptoms, therefore, would be particularly important indicators of depression if they are indeed likely to signal a mood disturbance.
Somatic Disruptions Following Childbirth Several features of the postpartum period are likely to cause the same somatic symptoms that sometimes accompany depressed mood. The disruptions to maternal sleeping schedules caused by nighttime feedings often make sleeping difficult even when the infant allows the mother to sleep (Lee, Zaffke, & McEnany, 2000). Consequently, about half of new mothers report significant insomnia (Ko et al., 2012). Sleep loss often leads to fatigue during the postpartum period (Rychnovsky & Hunter, 2009), as do reduced levels of ferritin and hemoglobin (Lee & Zaffke, 1999), which can result from pregnancy and/or childbirth (Milman, 2011). An estimated 42% to 59% of postpartum women experience substantial fatigue (Glazener et al., 1995; Lee & Zaffke, 1999). Changes in appetite vary. Women who breastfeed need, on average, an additional 670 calories per day (Dewey, 1997) and experience a concomitant increase in appetite. Women who do not breastfeed, or who stop doing so, will begin to need fewer calories, but the speed with which mothers’ eating patterns converge with their reduced caloric needs is quite variable (Lipsky, Strawderman, & Olson, 2012). All these factors can create uncertainty as to whether changes in energy level, appetite, and the ability to fall /stay asleep are likely to be indicative of depressed mood.
Irritability Following Childbirth Increased anger and irritability also are common features of the postpartum period. In fact, postpartum women are more likely to experience elevations in irritable mood than elevations in depressed or anxious mood (Bowen et al., 2012). Similar to fatigue, irritability during the postpartum period may be because of disrupted sleeping schedules (Kamphuis, Meerlo, Koolhaas, & Lancel, 2012), but it also may also be related to broader mood disturbance. Irritability and depression are strongly correlated in general populations and irritability commonly accompanies major depressive disorder (Fava et al., 2010). The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) does not include irritability as a criterion for major depressive disorder for adults but references to irritable mood appear frequently in the DSM’s qualitative description of that disorder.
Indicators of Postpartum Depression The present study was undertaken to address three questions pertaining to the validity of irritability, fatigue, insomnia, and appetite changes as indicators of depression in the
postpartum: (1) Do these symptoms show strong enough associations with depressed mood to constitute valuable indicators of depression? (2) Are the associations between these symptoms and depressed mood similar for postpartum women and non-postpartum women? (3) After accounting for depressed mood, do postpartum women experience higher rates of these symptoms than non-postpartum women? Question 1. Table 1 summarizes previously conducted studies bearing on Question 1. These studies have used a variety of depression measures and a variety of data analytic strategies. Cumulatively, they show that fatigue is consistently associated with depressed mood, as is irritability when irritability is assessed. The findings for changes in sleep and appetite are not uniform, though insomnia is generally correlated with depressed mood. Apparent from Table 1 is the fact that the majority of these instruments do not assess all four of the symptoms under our consideration. For instance, the Edinburgh Postnatal Depression Scale (EPDS; Cox, Holden, & Sagovsky, 1987), a commonly used measure for screening and research on postpartum depression, does not contain items for fatigue, appetite, or irritability. The EPDS was designed under the assumption that these symptoms could not be used to discriminate depressed from nondepressed women in the postpartum period. Should this assumption be incorrect, the EPDS and other instruments missing these symptoms would be less valid for having omitted them. In addition to inconsistent symptom coverage, the heterogeneity of the findings in Table 1 may be partly explained by unreliable measurement. With the exception of Beck and Gable (2001), the assessment instruments used in these studies use only one item to measure each depression symptom, a practice that is not optimal for establishing high reliability of measurement. In the research we describe here, we used the Inventory of Depression and Anxiety Symptoms (IDAS; Watson et al., 2007), which measures depressive symptoms with multi-item scales. Each of these scales has demonstrated high internal consistency and short-term retest reliability (Watson et al., 2007). Question 2. With the exception of Bernstein et al. (2008), the studies in Table 1 do not compare postpartum and non-postpartum women. This comparison is important because it allows us to determine whether indicators that perform poorly in the postpartum period do so because of something unique to that period or because they are generally weak markers of depressed mood. The item response theory analysis by Bernstein et al. (2008) was informative in this respect. They found that low energy and disrupted sleep showed associations of similar magnitude with underlying depression in their postpartum and non-postpartum groups, whereas the association between appetite changes and depression was significantly weaker among postpartum women.
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Williamson et al. Table 1. Are Insomnia, Fatigue, Appetite Changes, and Irritability Indicative of Postpartum Depression? Study Beck and Gable (2001)
Bernstein et al. (2008)
Bernstein et al. (2008)
Carvalho Bos et al. (2009) Kammerer et al. (2009)
Ross, Gilbert Evans, Sellers, and Romach (2003a) Ross, Gilbert Evans, Sellers, and Romach (2003b) Sugawara, Sakamoto, Kitamura, Toda, and Shima (1999)
Sample
Instrument
150 Postpartum women (46 with a diagnosis of major or minor depression) 95 Postpartum depressed women and 50 nonpostpartum depressed women 95 Postpartum depressed women and 50 nonpostpartum depressed women 354 Postpartum women
Postpartum Depression Screening Scale
16-Item Quick Inventory of Depressive Symptomatology–SelfReport 16-Item Quick Inventory of Depressive Symptomatology–SelfReport Beck Depression Inventory–II Structured Clinical Interview for DSM-IV
38 Postpartum depressed women and 606 postpartum nondepressed women 150 Postpartum women
150 Postpartum women
Edinburgh Postnatal Depression Scale Hamilton Rating Scale for Depression
1,002 Postpartum women Zung Self-Rating Depression Scale
Analysis
Insomnia
Fatigue
Appetite
Irritability
Significant correlation with depression diagnosis
Yes
N/A
Yes
Yes
Item–total correlations above .30
No
Yes
No
N/A
Item response theory (equivalent slopes in postpartum/nonpostpartum groups) Factor analysis (loadings above .40) Chi-square (do symptoms differentiate depressed vs. nondepressed) Principal component analysis (loadings above .40) Item–total correlations above .30
Yes
Yes
No
N/A
Yes
Yes
Yes
Yes
Yes
Yes
No
N/A
Yes
N/A
N/A
N/A
Yes
Yes
Yes
N/A
Yes
Yes
No
Yes
Item–total correlations above .30
Note. This table summarizes studies that bear on the validity of insomnia, fatigue, appetite disturbance, and irritability as indicators of depressed mood during the postpartum period. The last four columns indicate whether, based on the analysis and criteria described in column 4, a given indicator was found to be sufficiently associated with overall depression to be considered a valuable indicator. N/A indicates that the instrument used in a given study did not include a measure of the given construct.
Bernstein et al. (2008) did not measure irritability and their analysis focused on the statistical significance of the differences between the two groups rather than the substantive magnitude of those differences. We report effect sizes recently developed by Nye and Drasgow (2011) that identify those differences that are meaningful versus those that are insubstantial despite being statistically significant. These effect sizes are generated through multigroup confirmatory factor analysis (MG-CFA). MG-CFA and the IRT analyses used by Bernstein et al. (2008) yield similar information but MG-CFA is the appropriate framework for the present study because our indicators are scale scores rather than the item scores analyzed by Bernstein et al. (2008).
represent the expected value of an observed indicator at a given level of the latent factor. The MG-CFA analyses we use identify group differences in the average level of an observed indicator (in this case, a symptom) that cannot be accounted for by any group differences in the latent factor (overall depressed mood). Only Bernstein et al. (2008) have addressed intercepts. They found that when holding depression constant, postpartum women reported significantly more trouble sleeping than non-postpartum controls; the intercepts for appetite and energy were equivalent across groups. We build on Bernstein et al.’s (2008) analysis by using multi-item scales, calculating effect sizes, and adding a measure of irritability.
Question 3. We emphasize that Questions 1 and 3 are distinct. Irritability, fatigue, insomnia, and disturbed appetite may be more prevalent among the postpartum population (Question 3) and still be correlated with depressed mood (Question 1). Alternatively, we may observe similar rates of these symptoms between the two groups (Question 3) but find that the symptoms are not related to mood disturbance among postpartum women (Question 1). Question 3 cannot be resolved through the examination of item–total correlations or factor loadings but pertains instead to the intercepts of each indicator. Similar to regression, intercepts in CFA
Hypotheses Based on the findings outlined above, we expected to find that insomnia, fatigue, and irritability would be valid indicators of depressed mood during the postpartum period and would be related to it at least as strongly as in the general population of women. Because previous studies have yielded inconsistent findings regarding the validity of appetite disturbance as an indicator of depressed mood during the postpartum period, the degree to which appetite changes would be associated with depressed mood was treated as an
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Table 2. Depressive Symptoms Scales: Means, Standard Deviations, and Intercorrelations. Scale 1. Dysphoria 2. rWell-Being 3. Ill Temper 4. Lassitude 5. Insomnia 6. Appetite Loss 7. Appetite Gain 8. Suicidality
Postpartum, n = 271, mean (SD)
Non-postpartum, n = 820, mean (SD)
1
17.78 (7.51) 16.85 (6.64) 9.07 (4.27) 12.08 (4.84) 12.66 (5.74) 5.26 (2.88) 5.83 (3.08) 6.67 (1.74)
19.98 (7.86) 16.51 (6.82) 8.04 (3.64) 13.07 (5.21) 11.36 (4.88) 4.67 (2.32) 6.53 (3.06) 7.06 (2.29)
.47 .71 .71 .61 .40 .32 .52
2
3
.51 .64 .33 .40 .31 .53 .30 .51 .20 .27 .09 .24 .19 .40
4
5
6
7
.72 .52 .48 .42 .38 .24 .22 .15 .48 .43 .33 .36 .45 .36 .45 .52 .40 .25 .28 .40 .06 .38 .27 .21 .39 .22 .19 .11
8 .58 .36 .49 .44 .30 .24 .32
Note. Well-Being was reverse scored. Correlations below the diagonal are from the postpartum group, correlations above the diagonal are from the non-postpartum group. Bolded correlations are statistically significant at p < .05.
open question. We further anticipated that the baseline severity of all four symptoms would be higher among postpartum women, evidenced by higher intercepts for the corresponding indicators.
Method Participants and Procedures The 271 women in our postpartum sample were recruited through infant birth records from the state of Iowa and at maternal and child health centers in Iowa and Michigan. These women took part in a study that was originally aimed at developing a brief scale to detect postpartum depression (O’Hara et al., 2012). Mailed questionnaires were returned by 1,077 participants, and we selected all those completed within 12 weeks of the target child’s birth. A cutoff of 12 weeks postpartum was chosen in order to restrict our sample to women whose depressive symptoms were most likely to be affected by their recent childbirth while adhering to the recommendation by Meade, Johnson, and Braddy (2008) that each group included in multigroup analyses should exceed 200 observations. On average, these women were 27.9 years old (SD = 5.3) and 7.1 weeks postpartum (SD = 3.4). The vast majority were White (97%). Our non-postpartum sample was 820 women of childbearing age (defined as 18-45 years old) recruited in Iowa and Indiana as part of several studies on the factor structure of internalizing psychopathology (McDade-Montez & Watson, 2011; Watson et al., 2007; Watson et al., 2008; Watson et al., 2012). Their average age was 29.5 (SD = 7.8) and 88% of the women were White.
Measures Participants completed the eight depression scales of the IDAS (Watson et al., 2007). The IDAS scales were developed through factor analysis across many large samples, so that the composition of these scales reflects the factor structure of depression as observed from these analyses. Symptoms from
the preceding 2 weeks are measured on a 5-point scale from Not at all to Extremely. The Dysphoria scale (10 items) measures low mood, feelings of worthlessness, concentration problems, guilt, difficulty making decisions, and psychomotor disturbances. Although the composition of the Dysphoria scale may appear somewhat heterogeneous, these items consistently define a single, internally consistent latent factor (Watson et al., 2007). The Well-Being scale (8 items) assesses current levels of positive mood and satisfaction with life. The Ill Temper scale (5 items) measures irritability and anger. The Lassitude scale (6 items) measures low energy and hypersomnia. The Insomnia scale (6 items) measures difficulty falling and staying asleep. The Appetite Loss (3 items) and Appetite Gain (3 items) scales measure unusually low and high appetite, respectively. The Suicidality scale (6 items) measures self-harm and thoughts of suicide. All the IDAS scales have demonstrated good convergent validity with interviewer-rated measures of the same symptoms (Watson et al., 2007; Watson et al., 2008). They also showed good internal consistency in the community (αs = .77-.90) and postpartum samples (αs = .76-.89) used in the present analysis.
Analysis and Results The means, standard deviations, and intercorrelations for the eight IDAS depressive symptom scales in both groups are presented in Table 2. The community sample was missing data from 0.2% of the item responses and the postpartum sample was missing data from 0.1%. Prior to analysis, missing data were imputed using PROC MI in SAS version 9.2 (SAS Institute, Inc., Raleigh, NC). We used factor analysis to determine whether the eight depressive symptoms function as valid indicators of depression during the postpartum period. The construct of depression was conceptualized as a latent factor comprising the common variance among the eight symptoms. Factor analysis was conducted in Mplus 6.11 (Muthén & Muthén, 2010). Because our indicators were continuous variables with right-skewed distributions, we used maximum likelihood estimation with robust standard errors (the MLR estimator). The Well-Being
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Williamson et al. scale was reverse scored such that higher scores reflected lower levels of well-being. In accordance with Hu and Bentler (1999), we interpreted root mean square error of approximation (RMSEA) close to or below .06 and comparative fit index (CFI) close to or above .95 to indicate a good model fit. Scales with standardized factor loadings above .40 were interpreted as valuable indicators of depression (Clark & Watson, 1995). We then used a measurement invariance framework to compare the factor structure of depression in the postpartum and non-postpartum samples. Because our hypotheses pertained to the differential functioning of individual indicators rather than establishing the invariance of the IDAS as a whole, we used the free-baseline approach advocated by Stark, Chernyshenko, and Drasgow (2006). For the baseline model, we constrained the parameters of one referent indicator to equality while the parameters of the other seven indicators were free to vary between groups. The baseline model was then compared with seven constrained models in which a single parameter of one of the indicators was constrained to equality. Because our hypotheses concerned substantive differences between the postpartum and non-postpartum groups with respect to both factor loadings and intercepts, we tested for invariance in loadings and intercepts separately (Church et al., 2011). Although our hypotheses pertained only to the Ill Temper, Insomnia, Lassitude, Appetite Loss, and Appetite Gain scales, we examined the between-group differences for the parameters of all eight IDAS scales. We computed the difference in the CFI between the baseline and constrained models to evaluate invariance in each parameter. Chen (2007) has suggested that a difference of greater than or equal to .005 indicates a lack of invariance when the sample sizes of the two groups are not equal. Effect sizes representing the magnitude of nonequivalence between indicators were calculated using the dMACS computer program (Nye & Drasgow, 2011). We interpreted effect sizes using Cohen’s (1988) guidelines—effects below 0.2 are insubstantial, effects 0.2 to 0.5 are small, effects 0.5 to 0.8 are moderate, and effects above 0.8 are large.
Question 1: Indicators of Depressed Mood During the Postpartum We first used CFA to determine the strength of the associations between each depressive symptom and the latent construct of depressed mood. In CFA, these associations are represented by the factor loadings of an observed variable on an unobserved, or latent, variable that represents the common variance shared by all the observed variables. Previous factor analyses of the IDAS depression scales have demonstrated that a single latent factor accounts for the covariance between the scales, provided that the residuals of the Appetite Loss and Appetite Gain scales are
allowed to correlate (Nylen, Williamson, O’Hara, Watson, & Engeldinger, 2013). This model showed a good fit (RMSEA = .063, CFI = .964) in the postpartum sample. As Figure 1 shows, all the standardized factor loadings for the postpartum group were above .40 with the exception of Appetite Gain (λ = .35).
Question 2: Equivalence of Factor Loadings Before attempting to determine whether the factor loadings in the postpartum group were equivalent in magnitude to those in the non-postpartum group, we first needed to demonstrate that the factor structures in each group showed the same configuration. A factor structure demonstrates configural invariance across groups when that structure is composed of the same number of factors in each group and each of those factors is defined by the same indicators (Meredith, 1993). We tested the model that fit the postpartum sample using MG-CFA, allowing seven of the eight factor loadings and intercepts to vary between the groups. As recommended by Steenkamp and Baumgartner (1998), we constrained the factor loading and intercept of a referent indicator and fixed the mean of the non-postpartum group at zero to identify the model. The referent indicator was chosen based on a factorratio test (Cheung & Rensvold, 1999) in which the fit of 28 models comprising every possible combination of two indicators with constrained parameters (loadings and intercepts) was compared with the fit of a model in which only one indicator’s parameters were constrained. From the invariant set of indicators identified by the factor-ratio test, Dysphoria was chosen as a referent indicator because its standardized loading was most similar across the two groups when that parameter was allowed to vary. The configural model, presented in Figure 1, showed an adequate fit (RMSEA = .066, CFI = .959), suggesting that the broad structure of depressive symptoms is not different during the postpartum period. With configural invariance established, we then tested for metric invariance, which pertains to the equivalence of factor loadings across groups. Table 3 presents the parameters for the configural model with the change in CFI resulting from the constraint of each factor loading. As Table 3 shows, each constraint resulted in a ΔCFI of less than .005, meaning that we did not identify a lack of invariance for any of the loadings. The metric invariance model with all eight factor loadings constrained to equality across groups showed an adequate fit to the data (RMSEA = .066, CFI = .953).
Question 3: Equivalence of Intercepts Scalar invariance pertains to the equivalence of indicator intercepts across groups. In the baseline model for testing the scalar invariance of each indicator, all eight factor loadings were constrained to equality across groups, as was the
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Postpartum Depression
.95
Dysphoria
Well-Being
.48
.74
Ill Temper
.75
.65
Lassitude
Insomnia
.42
.35
Appe te Loss
.52
Appe te Gain
Suicidality
-.41
Non-postpartum Depression
.94
Dysphoria
Well-Being
.52
.69
Ill Temper
.76
.57
Lassitude
Insomnia
.50
.47
Appe te Loss
.61
Appe te Gain
Suicidality
-.38
Figure 1. Standardized factor loadings for the configural model.
Note. Well-Being is reverse scored. All coefficients are statistically significant.
Table 3. Indicator Parameter Discrepancies Between the Postpartum and Non-Postpartum Groups. Factor loading (λi) Scale Dysphoria rWell-Being Ill Temper Lassitude Insomnia Appetite Loss Appetite Gain Suicidality
Intercept (τi)
Postpartum
Non-postpartum
ΔCFI
Postpartum
Non-postpartum
ΔCFI
dMACS
−1.00 0.45 −0.44 −0.51 −0.52 −0.17 −0.15 −0.13
−1.00 0.48 −0.34 −0.54 −0.37 −0.16 −0.20 −0.19
— .000 .003 .000 .003 .000 .000 .001
19.98 22.16 10.04 13.20 13.81 5.64 6.16 7.00
19.98 23.49 8.04 13.07 11.36 4.67 6.53 7.06
— .004 .021 .001 .014 .009 .001 .000
— 0.09 0.37 0.01 0.36 0.23 0.12 0.14
Note. Well-Being was reverse scored. All parameters are unstandardized. Bolded parameters differed significantly (ΔCFI ≥ .005) across groups.
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Williamson et al. intercept for dysphoria. The intercepts were then tested for lack of invariance one by one in the same manner as the factor loadings. Table 3 shows the unconstrained intercepts from the configural model along with the change in CFI corresponding to the invariance test for each of them. These tests showed that the intercepts for three indicators were significantly different (ΔCFI ≥ .005) between the groups: The intercepts for Ill Temper, Insomnia, and Appetite Loss were all higher in the postpartum group. The partial scalar invariance model with these three intercepts freed showed an adequate fit (RMSEA = .066, CFI = .949). Finally, we input the unstandardized parameters from the configural invariance model into the dMACS computer program to ascertain the magnitude of invariance in the indicators. The generated effect sizes take into account invariance in both loadings and intercepts. We observed small differences between the groups for the Ill Temper, Insomnia, and Appetite Loss scales; the differences for the other five scales were insubstantial (Table 3). The dMACS program also identifies the impact of the cumulative lack of invariance for all parameters on the difference between the means of the latent variables. Our analyses showed that the mean of the latent depression score was 33.63 (SD = 19.32) in the postpartum group and 27.24 (SD = 19.06) in the non-postpartum group but that noninvariance in the indicators lead to an overestimation of the postpartum mean by 1.95. The difference between the sum of the IDAS depression scales for postpartum women and the sum of the IDAS depression scales for non-postpartum women does not accurately reflect the difference in depressed mood between postpartum and non-postpartum women. The sum of the IDAS depression scales for postpartum women is inflated by an average of 1.95 points because of elevations in Ill Temper, Insomnia, and Appetite Loss during the postpartum period that are not related to depressed mood.
Discussion Summary and Interpretation of Results Based on conventional standards, all the IDAS depression scales were valuable indicators of depressed mood during the postpartum period with the exception of appetite gain, which showed an equivocal loading on the latent depression factor. However, the loading for appetite gain in the postpartum sample was not significantly different from that of the non-postpartum sample. This finding is consistent with other studies of depression in the general population that suggest that increases in appetite and weight are ambiguous criteria for major depressive disorder (McGlinchey, Zimmerman, Young, & Chelminski, 2006). We found no significant differences between the postpartum and non-postpartum groups in the degree to which
any of the symptoms of interest were related to depression. Similar to Bernstein et al. (2008), we found that postpartum women reported higher baseline levels of insomnia. Unlike Bernstein et al. (2008), we observed that postpartum women also reported higher baseline levels of appetite loss, and irritability. Controlling for level of depressed mood, the severity of fatigue and appetite gain were equivalent across the groups.
Implications of the Findings Our findings do not support the use of increased appetite as an indicator of depression during the postpartum period but do support the inclusion of indicators for insomnia, fatigue, decreased appetite, and irritability. These results are particularly notable given that many of the instruments used to screen and assess postpartum depressive symptoms, including the popular EPDS, do not include such indicators. The results also reinforce calls by other investigators to include questions about irritability as part of any comprehensive depression assessment (Fava et al., 2010). We note that irritability during the postpartum period appears to abate in response to the same cognitive behavioral interventions that are effective for depression (Marrs, 2013). The higher intercepts for insomnia, appetite loss, and irritability indicate that a given level of one of these symptoms would not suggest the same level of depressed mood in postpartum women as it would for women in the general population. For example, a postpartum woman who scored a 15 on the IDAS Insomnia scale is likely to be experiencing less depressed mood than a non-postpartum woman with an Insomnia score of 15. A score of 15 on the IDAS Insomnia scale for a postpartum woman would indicate about the same level of depressed mood as a score of 13 for a non-postpartum woman. In the same way, it is likely that a postpartum woman’s score of 2 on the sleep disturbance item of the Patient Health Questionnaire-9 (Kroenke, Spitzer, & Williams, 2001) is not equivalent to a non-postpartum woman’s score of 2. In sum, questions about irritability, insomnia, and loss of appetite should be included in any assessment of postpartum depression, but higher scoring thresholds for these items may lead to more valid overall scores when doing screening and research. With large, representative samples, both MG-CFA and item response theory analyses can be used to norm screening and research instruments and create simple scoring algorithms that take into account the expected elevations in these symptoms.
Strengths and Limitations Our investigation benefitted from sample sizes that were larger than most of the previous studies on this topic. Rather than using potentially unreliable single-item indicators for
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our constructs of interest, we used multi-item scales with established retest reliability and good internal consistency in the present samples. Additionally, our instrument was more comprehensive than others used by previous researchers and we calculated effect sizes for interpreting the magnitude of the differences between our postpartum and non-postpartum groups. With respect to the study’s limitations, we emphasize the correlational nature of these findings. For instance, based on the substantial factor loading for insomnia on depression, we cannot determine the extent to which depressed mood causes insomnia or the extent to which lack of sleep causes depressed mood. Interestingly, cognitive behavioral treatment of postpartum insomnia has been shown to alleviate depressive symptoms (Swanson, Flynn, Adams-Mundy, Armitage, & Arnedt, 2013). We also note that depressive symptoms were measured exclusively through self-report, and the associations between these symptoms likely were inflated by common method variance. Additionally, our two samples contained limited diversity. It is unlikely that more diverse samples would yield substantively different results, however, given that the characteristics of depression indicators under our analysis appear to be generally invariant across demographic groups (Golding & Aneshensel, 1989; Gregorich, 2006). Finally, the IDAS is strongly related to clinical impairment (Watson et al., 2008), but investigators have yet to clarify the range of IDAS scores that suggest treatment for depression is warranted. Therefore, although we can say, in relative terms, that insomnia (along with irritability and appetite loss) must be more severe in postpartum women for it to indicate depressed mood, we cannot say how severe insomnia must be, in absolute terms, before it is likely to indicate a mood disturbance that demands clinical intervention.
Conclusion A comprehensive assessment of depressive symptoms during the postpartum period should include questions about insomnia, fatigue, loss of appetite, and irritability. Insomnia, appetite loss, and irritability indicate depressed mood only at higher levels than outside the perinatal period. Future research is needed to establish the severity of depressive symptoms that identify postpartum women who are in need of psychological treatment. Acknowledgments We thank Lisa Segre and Jennifer McCabe for their help in the preparation of this article.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Support for this research was provided by the Centers for Disease Control and Prevention (MM-0822, S. Stuart, PI) and by the National Institute of Mental Health (MH068472, D. Watson, PI).
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