The psychometric properties of the subscales of the GHQ-28 in a multi-ethnic maternal sample: results from the Born in Bradford cohort

Born in Bradford (BiB) is a longitudinal multi-ethnic birth cohort study aiming at examining the impact of environmental, psychological and genetic factors on maternal and child health and wellbeing [20]. Bradford is a city in the North of England with high levels of socio-economic deprivation and ethnic diversity. Women were recruited prior to a glucose tolerance test offered as a routine procedure to all pregnant women registered at Bradford Royal Infirmary at 26–28 weeks gestation. A baseline questionnaire was administered to women who consented via an interview conducted in a designated room with semi-private booths. Women could choose to have their interview conducted in either English, Mirpuri (a spoken variant of Punjabi) or Urdu. Women not able to converse in any of these three languages were eligible to enrol but did not complete the baseline questionnaire and thus are not included here. The full BiB cohort recruited 12,453 women during 13,776 pregnancies between 2007 and 2010 and the cohort is broadly characteristic of the city’s maternal population. Ethical approval for the data collection was granted by Bradford Research Ethics Committee (Ref 07/H1302/112).

Two samples from the BiB cohort were used to explore the properties of the GHQ-28. First we report on data from 5,299 women with singleton births enrolled between November 2007 and March 2009 who completed the phase two version of the three versions of the baseline questionnaire. Second, we used a subset of the cohort, known as BiB1000, to assess the structure of the GHQ-28 in pregnancy and postnatally. BiB1000 participants in our sample were enrolled between August 2008 and March 2009, completed the phase two baseline questionnaire and consented to repeat visits at six, 12, 18, 24 and 36 months postpartum. We report on the antenatal and six-month GHQ-28 data for 1,305 women with singleton births.

An initial Urdu translation of the GHQ-28 questionnaire was adapted for use as a script in this population by a professional translator through a process of refinement using participatory methods [21, 22]. Assessment of understanding was undertaken with groups of bilingual then monolingual Urdu women from local Children’s Centres. A Mirpuri version was transliterated from a second draft that used a similar iterative process with bilingual then monolingual Mirpuri speaking women. Scripts were finalised from the third draft version in each language.

The GHQ-28 was administered on paper as part of a self-completion module at the end of the interview for women who chose to complete their baseline questionnaire in English. For the women who chose Mirpuri or Urdu language, the GHQ-28 questions were read aloud and the research assistant coded the response on paper. Verbal administration was necessary because there is no written form of Mirpuri, and not all Urdu speakers are fluent in reading and writing the Urdu language. Some of the women were accompanied; therefore verbal responses may have been audible to the accompanying person. For the women in BiB1000, the six-month GHQ-28 was administered in the women’s home by research staff in the language of choice.

The GHQ-28 has a 4-item response scale anchored (typically) with ‘Not at all’, ‘No more than usual’, ‘Rather more than usual’, and ‘Much more than usual’. Several scoring options are available; we used the Likert method to indicate symptom severity, which scores the item response between 0–3 (0–1–2–3, subscale range 0 to 21) as this is the recommended method for assessment of the subscales. We excluded the few cases where either the GHQ-28 was missing in its entirety, or did not contain at least one intact subscale.

Questions relating to ethnicity in BiB were based on those used in the UK’s 2001 census and comprised of one question that asked which ethnic group the mothers considered they belonged to (White, Mixed ethnic group, Black or Black British, Asian or Asian British, Chinese or other), followed by a further question, based on their response, about their cultural background. For example, if a participant selected ‘Asian or Asian British’ as ethnic group, a choice of cultural background could be selected from the following; Indian, Pakistani, Bangladeshi, Indian Caribbean, African-Indian. Self-defined ethnic and cultural group information was taken from the baseline questionnaire and classified into the two most numerous groups of White and Pakistani; all other responses were coded into a separate category (Other). The few cases of women identified as mixed White and Pakistani (N = 18 in the cohort) were classified in the White group. Due to the low number of non-UK born White women (N = 146) we did not further differentiate the cultural background of those who identified as White.

The interviewer recorded the language in which the interview was conducted.

We tested for measurement equivalence on the subscales by multi-group confirmatory factor analysis (CFA), using Mplus version 7 with a robust maximum likelihood (MLR) estimator as our data were not normally distributed. MLR is a full information estimator that employs all the available data and thereby calculates unbiased parameter estimates in the presence of data which are missing at random or missing completely at random [23]. Some women completed the instrument on more than one occasion due to multiple pregnancies. This introduces non-independence into the sample, which can lead to incorrect values for standard errors and fit statistics (fit statistics based on chi-square). We accounted for this minor clustering of the full cohort data by utilising a sandwich estimator (the cluster command within Mplus, combined with the complex samples approach). We fitted increasingly restrictive pairwise models in five subpopulations; women who completed the questionnaire in English for the ethno-cultural groups of Pakistani, White and Other, women who completed the questionnaire in Mirpuri (Pakistani and Other), and women who completed it in Urdu (Pakistani and Other). As a subscale score is calculated independently from other subscales in practice, we considered the fit of each subscale separately for each subpopulation, with no cross-loading items permitted. If a factor was not associated with the same item sets across groups (i.e. configural invariance was not met) a model generation strategy was used where items within subscales were removed until adequate fit was achieved for each subpopulation for the same items for each factor. We considered model fit adequate if thresholds for three indices were met; comparative fit index, CFI (≥0.95), root mean square error of approximation, RMSEA (≤0.08) and standardised root mean square residual, SRMR (≤0.06). We interpreted modification indices to help identify the most problematic items and accepted the solution that retained the largest number of items, for the best fit, across groups. If configural invariance was then indicated, we tested whether the strength of the relationship between each item and the factor were equal across groups by constraining factor loadings to be equal across both groups (metric invariance). If metric invariance was indicated we then tested for scalar invariance by also constraining item intercepts to be equal [24‐26]. For analysis purposes the latent variable is assigned the scale of the first item. If there is variation in how each group responds to an item response scale, a unit change in a factor score will be associated with an unequal change in the score of an item across groups. The presence of this Differential Item Functioning (DIF) indicates that between group comparisons will be invalid [27].

We treated the data as continuous for analysis purposes. Likert data can be treated as continuous, or can be considered to be ordered categorical (i.e. an item response theory – IRT-based approach). There is debate in the literature regarding the most appropriate method for analysing such data [28, 29] however our aim was to analyse the scales in the same metric in which they are employed. The scales are typically scored by summing (or equivalently averaging) items, not scored using IRT-based methods, hence we analysed the covariance matrix.

We repeated this process (configural, metric, scalar testing) on the subsample of women who completed the measure both during pregnancy and six-months postpartum (BiB1000). We restricted the BiB1000 analysis to those women who completed both questionnaires in the same language. Two women from the ‘Other’ ethnic groups did not complete the questionnaire in English and only three women completed the GHQ-28 in Mirpuri. Therefore, our analysis compared these data across four ethnic groups; English administration for White women, English (Pakistani), English (Other) and Urdu (Pakistani).

As noted previously, we considered model fit adequate if thresholds for three indices were met; CFI (≥0.95), RMSEA (≤0.08), and SRMR (≤0.06). We did not interpret change in χ ² as an indicator of invariance in increasingly restrictive models as it is relatively insensitive to change in large samples. Instead we used a change in CFI of ≤0.01 together with a change in SRMR of ≤0.03 to indicate substantive invariance, setting the SRMR criterion to ≤0.01 when evaluating scalar invariance [30, 31].

As the same seven items were not associated with the same factors across groups, i.e. configural invariance was not indicated, we followed up the CFA of the BiB cohort with exploratory factor analysis (EFA). We specified an EFA with between 1 and 8 latent variable solutions as implemented in Mplus. To determine the most parsimonious solution that best fit the data we examined the scree plot [32] for the point of inflexion and used the fit criteria detailed above.

The results from the CFA suggested greater variability between English and non-English groups than for pairwise comparisons between the White British, Pakistani and women of other ethnicities who completed the questionnaire in English. We hypothesised that this was due to differences in the underlying factor structure between linguistic-cultural groups and used EFA to investigate this possibility. A better fit was indicated for a five factor model over a four-factor for the sample overall and all English groups, and six factors over five for the Urdu and Mirpuri groups. However, the individual items making up these factors appeared to differ (Table 6). Across the cohort there appeared to be two concepts being measured with the somatic questions; one cluster of items relating to generalised somatic symptoms (items 1–4), and one relating to the two items concerning physical symptoms in or on the head (items 5 & 6, dubbed Head Somatics in Table 4). The depression concept was split into two factors for the women who responded to the Mirpuri version of the GHQ-28. Several items did not load onto any factor (factor loading <0.3) or loaded only weakly (<0.4); in particular Items 7 (hot/cold spells) 15 (busy and occupied) and 21 (enjoy normal activities), indicating little relevance to the observed factors in most of the subpopulations.

The amount of variance in the overall model explained by the factors was low; from 41.1% for the Pakistani (English) group, to 32.6% of the Urdu responses. The Severe Depression and Anxiety and Insomnia factors accounted for the largest proportion of the variance for most of the groups. The exception was for the Urdu sample, where the Anxiety and Insomnia questions did not appear to be a unified concept and accounted for less of the variance.

Irrespective of cultural background, it is common for people with depression to initially present with somatic symptoms e.g. [14, 41]. Somatisation of psychological distress is of interest in maternal populations where new and perhaps unfamiliar bodily changes coincide with any onset of distress. Such simultaneous physical and hormonal changes may complicate self and clinical recognition of potential affective distress. For example, somatic dysfunction might be construed as causative of distress, distress could be overshadowed by physical symptoms that may be considered to have more serious implications for the baby’s health, or body symptoms may simply co-exist alongside with distress. Neither is the concept of somatisation uni-dimensional. Simon et al. [41] define three different presentations; patients with psychological distress who initially present somatic symptoms, those distressed who present with medically unexplained somatic symptoms and those who present somatic symptoms and deny psychological distress. Bhui et al. [14] adds a fourth; presentation of somatic symptoms made significantly made worse by feeling low, stressed or anxious. The topic has generated much theoretical interest for South Asian cultures where somatisation has sometimes [42], but not universally [13, 41], been reported to be more frequently endorsed as a symptom of depression. Indeed some data indicate that initial presentation with somatic symptoms might be a function of the patient-doctor interaction rather than a cultural phenomenon [41].

Our data show that broadly, across the maternal population, two concepts related to somatic symptomology were evident; the first comprised of generalised somatic symptoms and the second of symptoms related to the head. A principle components evaluation of a non-maternal European sample with rheumatoid arthritis [43] found a similar split in structure, but a study of pregnant Nigerian women [19] reported that all seven somatic items clustered together. Although there are differences in methodology, this indicates that the split between general and specific somatic symptoms may be related to factors other than maternity, or female gender, and in our study these elements appear stable regardless of ethnic background, language of administration or pregnancy/postnatal status. We suggest that this hypothesis is tested in other population samples.

Antenatal anxiety commonly co-occurs with depression and is antecedent to postnatal anxiety and depression [9, 44‐46], and our EFA implicated this factor as the largest symptom cluster for most groups. However, the invariance testing indicated some significant problems with comparisons involving the Urdu group, which the EFA revealed was likely due to a split in the underlying concept.

For all groups except the Urdu language groups, the concept of Social Dysfunction was related to all its hypothesised items, confirming the findings in a Nigerian antenatal sample [19]. Excluding comparisons with the Urdu group, this factor also appeared to indicate pairwise invariance. However, the clinical relevance of this subscale is not well researched [47], which limits its relevance in distinguishing psychiatric morbidity from the range of normal changes during pregnancy.

As noted, anxiety and depression are commonly co-morbid and these two GHQ-28 factors are unsurprisingly correlated, although the depression subscale has been found to garner some additional information [47]. Here it is noteworthy that this subscale measures severe depression with three questions relating to suicidal ideation; notably absent are enquiries into dysphoric mood. Measurement of such a dimension is of interest inter-culturally; Bhugra and colleagues have enumerated that in London, young South Asian women are at higher risk for presenting with attempted suicide than White women [48, 49] with cultural and family conflict the actual and perceived causes of such attempts [48, 50]. However, the utility of this subscale to measure the concept of suicidality might be limited, as although for the antenatal English language and Urdu respondents the questions seemed unified and the factor important, this was not the case in the Mirpuri group, and there was evidence of invariance between groups. Furthermore, only one of the suicidality questions (item 25) was invariant between groups. Model estimation difficulties that may have been related to low endorsement of these severe items precluded analysis of postnatal data.

After reducing items to create factors which appeared to have reasonable fit across all the subpopulations, the iterative process of invariance testing revealed systematic differences in how the different subpopulations rated themselves on the measurement scales. We would be able to solve the problem of systematic differences in scale response if, as in most CFA analyses, there were just two populations to compare; but due to both cultural and language variation we identified five distinct groups, and as the DIF varied within sub-group pairs, systematic correction is unfeasible. While some of the differences are small and would have a negligible impact on mean scores, some differentials are up to half a point (on a four-point scale) which has the potential to lead to spurious conclusions after comparison.

Interpretation of the analysis into any systematic differences in structure between antenatal and postnatal administration were limited due to difficulties with model estimation, particularly in the Severe Depression subscale.

Our sample is representative of the maternal community in Bradford, and included a large number of South Asian minority women for whom relatively little is known about mental health in pregnancy. Further, we applied a rigorous approach to our analysis; however, our study does have some shortcomings.