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Kasekeetal. BMC Res Notes (2019) 12:110
https://doi.org/10.1186/s13104-019-4151-1
RESEARCH NOTE
A structural equation modelling
ofthebuering eect ofsocial support
onthereport ofcommon mental disorders
inZimbabwean women inthepostnatal period
Tanaka Kaseke1 , James January2 , Catherine Tadyanemhandu1,3 , Matthew Chiwaridzo1,4
and Jermaine M. Dambi1,4*
Abstract
Objective: Globally, 13–20% of women experience a common mental disorder (CMD) postnatally. Unfortunately,
the burden of CMDs is disproportionally substantial in women from low-income countries. Nevertheless, there is a
growing recognition of the buffering effect of social support (SS) on psychiatric morbidity and the need for mental
well-being support services/interventions. This study evaluated the relationship between psychiatric morbidity and SS
levels, and factors influencing the mental health functioning of Zimbabwean women postnatally. Data were collected
from 340 mothers and were analysed through structural equation modelling.
Results: The mothers’ mean age was 26.6 (SD 5.6) years. The mean Multidimensional Scale of Perceived Social Sup-
port score was 42.7 (SD 10.8), denoting high levels of SS. Additionally, 29.1% of the population reported excessive
psychiatric morbidity, the median Shona Symptoms Questionnaire score was 5 (IQR: 2–8). The structural equation
model demonstrated the buffering effects of SS on psychiatric morbidity (r = − 0.585, p = 0.01), and accounted for
70% of the variance. Being unmarried, increased maternal age, lower educational and income levels were associated
with poorer maternal mental health. There is a need for routine; surveillance and treatment of CMDs in women in the
postnatal period, including integration of low-cost, evidenced-based and task-shifting SS interventions.
Keywords: Women, Postnatal, Social support, Mental health, Zimbabwe
© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
(http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/
publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Introduction
Globally, between 13 and 20% of women who have just
given birth experience a mental disorder [1]. Postnatal
depression is particularly endemic and is a leading cause
of disability in child-bearing women [2]. Other postna-
tal mental disorders such as anxiety, postnatal blues and
psychosis are also prevalent [3]. Unfortunately, the bur-
den of common mental disorders (CMDs) such as mater-
nal depression is disproportionally higher in low-income
countries as opposed to high-income countries with
estimated prevalence rates of 19.8% and 10% respectively
[4]. For example, 30–34.2% of urban-dwelling, Zimba-
bwean women suffer from postnatal depression (PND)
[5–7]. Poverty, lower education, compromised physical
health, a history of a CMD, intimate partner violence,
inadequate social support, and changing cultural prac-
tices are important predictors to poor mental health sta-
tus in women who have just given birth [6, 8–11].
Despite the significant burden of CMDs among women
in Sub-Saharan Africa, in-depth information on men-
tal health issues in the postnatal period is limited [7,
12]. Nevertheless, there is a growing recognition of the
importance of social support (SS) in improving the men-
tal health of women in the postnatal period [11, 13].
For instance, the buffering hypothesis postulates that
Open Access
BMC Research Notes
*Correspondence: jermainedambi@gmail.com; dmbjer001@myuct.ac.za
1 Department of Rehabilitation, University of Zimbabwe, College
of Health Sciences, P.O Box A178, Avondale, Harare, Zimbabwe
Full list of author information is available at the end of the article
Page 2 of 7
Kasekeetal. BMC Res Notes (2019) 12:110
effective psychological and social resources, particularly
social stability, social participation, adequate emotional
and instrumental support, can be considered protective,
i.e. they buffer the impact of life stress on the psychologi-
cal well-being of the mother [14, 15]. On the contrary,
a lack of SS can lead to adverse outcomes such as; low
birth weight, preterm labour, foetal neural tube defects,
depression and anxiety [16]. However, there is a pau-
city of information on the extent to which SS influences
maternal mental health in low resource-settings [7]. e
current study therefore set out to identify sources of SS
and evaluate the buffering effects of SS on the report of
CMDs in urban-dwelling, Zimbabwean women in the
postnatal period.
Main text
Study design, research setting andparticipants
We conducted a cross-sectional study at Harare City
Council primary health centres. e clinics offer a variety
of health services including: curative, maternity and post-
natal care. Six clinics were purposively selected to ensure
recruitment of participants across the socio-economic
continuum. Two of the six clinics were in low to medium
density catchment areas with four clinics being located
in high-density suburbs [17]. Assuming a 33% prevalence
of PND in urban-dwelling, Zimbabwean women [6], the
minimal sample size was 340 at 95% confidence interval
and 80% goal power. Women who were seeking postnatal
services and willing to participate on the day of data col-
lection were conveniently selected. Included were biolog-
ical mothers ≥ 18years with children aged 52weeks and
below. Mothers with a confirmed diagnosis of a mental
health disorder and or suffering from long-term health
conditions such as HIV/AIDS, cancer, among others were
similarly excluded as this could have confounded the
study outcomes. Mothers not proficient in either English
or Shona languages were similarly excluded due to lack
of financial resources for translating study outcomes into
other languages.
Study instruments
A purpose-built questionnaire was used to capture the
participants’ age, gender, marital status, educational level,
employment status and perceived level(s) of income. e
Shona Symptom Questionnaire (SSQ), an indigenous
generic screen, was used to evaluate the report of CMDs
in the past 7days. e SSQ is a binary outcome i.e. “yes”
and “no” responses are scored as one and zero respec-
tively. e score range is 0–14 and scores ≥ 8 indicate
risk of CMDs. e SSQ is especially sensitive in screen-
ing for depression and anxiety and has been extensively
validated in the research setting [18, 19]. e Multidi-
mensional Scale of Perceived Social Support (MSPSS),
a 12-item outcome was used to measure SS. Respond-
ents rate the extent of satisfaction with the SS received
from friends, family and significant other. Responses are
ranked on a five-point Likert scale which ranges from
“strongly disagree = 1” to “strongly agree = 5”. e MSPSS
is one of the extensively used SS outcomes [20] and has
been translated and validated into Shona (a Zimbabwean
native language) [21, 22].
Procedure
After receiving ethical and institutional approvals, the
principal investigator (TK) approached prospective par-
ticipants in the treatment waiting area(s). e researcher
explained the study rationale, applied the selection cri-
teria in recruiting participants and afterwards issued a
detailed information sheet to mothers meeting the inclu-
sion criteria. Mothers were obliged to provide written
consent to participate in the study. All outcomes were
primarily self-administered, however, the principal inves-
tigator aided participants where necessary.
Data analysis andmanagement
Data were entered into Microsoft Excel and analysed
using STATA (Version 15). Normality was checked using
the Shapiro–Wilk Test. Descriptive statistics (frequen-
cies and means) were used to describe participants’ soci-
odemographics and responses on the SSQ and MSPSS.
ereafter, univariate analysis (t-tests, co-relation co-
efficiencies and analysis of variance tests) was applied to
determine factors influencing mothers’ mental health.
Contextual factors (patients characteristics) and study
primary outcomes (SSQ and MSPSS sub-scores) were
then entered into the structural equation model as
endogenous and exogenous variables respectively. e
following parameters were set as a minimum criterion for
model fit; Likelihood Ratio Chi squared Test (χms2)—cri-
terial value: p > 0.05, root mean square error of approxi-
mation (RMSEA)—criterial value: ≤ 0.06, Comparative
Fit Index (CFI)—criterial value: ≥ 0.90, Tucker–Lewis
Index (TLI)—criterial value: ≥ 0.90 and the standard-
ized root mean square residual (SRMR)—criterial value:
≤ 0.06 [23].
Results
Many of the mothers were; married (56.8%), attained
secondary education (83.4%), unemployed (65%) and
reported of medium levels of income (55.3%). eir chil-
dren were mostly males (50.9%), with an average age of
22.6 (SD 13) weeks. Mothers received the least and great-
est amount of social support from friends and family
respectively, and the mean MSPSS score was 42.7 (SD
10.8), denoting high levels of SS. Additionally, 29.1% of
the mothers showed excessive psychiatric morbidity and
Page 3 of 7
Kasekeetal. BMC Res Notes (2019) 12:110
the median SSQ score was 5 (IQR: 2–8) (Table1). See
Additional files 1 and 2 for frequencies of reported prob-
lems on the MSPSS and SSQ respectively.
Illustrated in Fig.1 is the model explaining the buff-
ering effects of social support on psychiatric morbidity
(r = − 0.585, p = 0.01) and the associated contextual fac-
tors. e model accounted for 70% of the variance (See
Additional file3) and displayed excellent fit as outlined in
Table2. Being unmarried, lower education status, lower
income level, and increased maternal age were associated
with poorer maternal mental health.
Discussion
Consistent with previous studies, outcomes from the pre-
sent study suggests that mothers who received a greater
amount of SS were likely to have optimal mental health
[11, 13]. Lack of SS is a demonstrated risk factor for psy-
chiatric symptomatology in the postnatal period [24, 25].
Significant others and family were cited as the greatest
sources of SS with friends providing the least support.
Previous studies have shown that it is not always possi-
ble for women to differentiate the effects of spousal sup-
port from other kinship members. In collectivist cultures
like Zimbabwe, the terms husband/significant other and
family are habitually used interchangeably [26]. Further,
mothers were likely to have decreased networking oppor-
tunities due to the demands of caring for the new infant,
and this may further explain the discrepancies in sources
of SS [25, 27].
e prevalence of CMDs (29.1%) was relatively higher
compared to the global lifetime prevalence of 18% [28],
and a 16% prevalence yielded from an almost similar,
previous local study [29]. e changing patterns of men-
tal health symptomatology in Zimbabwe especially given
the advent of the HIV/AIDS pandemic and the worsen-
ing economic challenges the country has been facing
may account for the dissimilarity [7]. Poverty, poor nutri-
tion, inmate partner violence, history of depression, lack
of spousal support, unstable marital status, unplanned
pregnancies and increased social responsibilities are risk
factors for increased psychiatric morbidity in the post-
natal period for women residing in low-resource settings
[11, 13, 24, 30–33].
In our study, having fewer resources (lower education
and lower income), small social network (being unmar-
ried) and maternal characteristics (increased maternal
age) negatively influenced maternal mental health. Mar-
ried and cohabiting mothers showed the least risk of
psychiatric morbidity. Traumatic experiences such as
the death of a loved one, losing a job and relationship
Table 1 Participants descriptive statistics, N = 340
a Results not presented in the n (%) format
Variable Attribute Frequency, n (%)
Age of child in weeksaMean (SD) 22.6 (SD 13.0)
Gender of child Female 167 (49.1)
Male 173 (50.9)
Mother’s ageaMean (SD) 26.6 (5.6)
Marital status Married 193 (56.8)
Co-habiting 101 (29.7)
Other 46 (13.5)
Level of education Primary 20 (5.8)
Secondary 286 (83.4)
Tertiary 34 (9.9)
Employment status Formally employed 40 (11.8)
Self-employed 77 (22.6)
Unemployed 223 (65.0)
Perceived level of income Below average 88 (24.1)
Average 188 (55.3)
Above average 70 (20.6)
Social support (MSPSS) scoresaFamily [mean (SD)] 3.8 (SD 0.9)
Friends [mean (SD)] 3.1 (SD 1.2)
Significant other [mean (SD)] 3.8 (SD 1.0)
Summative score [mean (SD)] 42.7 (SD 10.8)
Psychiatric morbidity (SSQ) scoresaSSQ scores ≥ 8 [n (%)] 99 (29.1%)
Summative score: median [Q1–Q3] 5 [IQR: 2–8]
Page 4 of 7
Kasekeetal. BMC Res Notes (2019) 12:110
breakdown or divorce are associated with poor mental
health functioning [34–36]. ese events are suggested to
reflect additional stress after childbirth, at a time during
which women are especially vulnerable [36, 37]. Mothers
with higher levels of education reported higher levels of
SS. Being educated is an important predictor to greater
political and social engagement [38]. Education increases
the sense of control that an individual feel over their life
and concomitantly increases the chances of accessing
stable relationships and expanded social networks which
ultimately enhances the amount of the SS received [36,
38]. Further, educated mothers are highly likely to be
employed and our findings also revealed that mothers
with higher levels of perceived income indicated the least
risk of psychiatric morbidity. ese findings are in keep-
ing with a previous systematic review which revealed that
socio-economic disadvantaged women are five times pre-
disposed to CMDs in the perinatal period [1].
Fig. 1 Mothers’ mental health model showing the relationship between perceived levels of social support, report of common mental disorders and
contextual/demographic factors
Table 2 Model t indices, N = 340
Fit statistic Index Criterion fort Result-interpretation
Likelihood ratio Chi squared test (χms2)p > 0.05 χ2 (df 24) = 84.87, p < 0.001—misfit
Normed Chi square [χ2/df]χ2/df < 2 3.5—misfit
Population error Root mean squared error of approximation (RMSEA)-(90% CI) RMSEA ≤ 0.06 0.054 (0.026: 0.080)—good fit
Information criteria Akaike’s information criterion (AIC) The smaller, the better 8965.5—best fit
Bayesian information criterion (BIC) The smaller, the better 9080.32—best fit
Baseline comparison Comparative Fit Index (CFI) CFI ≥ 0.90 0.928—good fit
Tucker–Lewis Index (LFI) LFI ≥ 0.90 0.893—good fit
Size of residuals Standardized root mean squared residual (SRMR) SRMR ≤ 0.08 0.056—good fit
The coefficient of determination (SD) The greater, the better 0.7—good fit
Page 5 of 7
Kasekeetal. BMC Res Notes (2019) 12:110
Current evidence also suggests that increased mater-
nal age is a risk factor for CMDs and this is in contra-
diction to previous studies [6, 24, 30, 32, 33]. It has been
previously hypothesized that younger mothers are at an
increased risk for CMDs as they may not be fully pre-
pared for the parenting role. Further, in certain instances,
the lack of SS especially spousal support, may predis-
pose younger mothers to poor mental health function-
ing as some of the pregnancies maybe unplanned [24,
30]. Older mothers are likely to have greater financial
resources, greater education and more likely to be mature
and these are protective factors against CMDs according
to the buffering hypothesis [39]. On the contrary, fertility
problems, delayed parity, and prior obstetric complica-
tions are likely to predispose older mothers to CMDs [31,
40]. Further, older mothers may not receive adequate SS
in comparison to first-time mothers, older mothers may
be deemed “proficient” in infant care, and this predis-
poses them to an increased risk of CMDs [31, 40]. Other
studies did not find any association between maternal age
and CMDs [6, 35, 39, 41]. Considering the inconclusive
evidence from literature, there is a need for further lon-
gitudinal and qualitative studies to understand the effects
of maternal age on the prevalence of CMDs further.
Collectively, our study outcomes point out the need
for the provision of support services such as professional
counselling for the improvement of the mental health
of mothers in the postnatal period. However, the lack of
human resources is a massive threat towards the closure
of the huge mental health treatment gap in low-resource
settings [42]. is therefore calls for the integration of
low-cost, evidenced-based and task-shifting interven-
tions such as the Friendship Bench (FB) [43] in mitigating
the burden of CMDs in this populace. e FB concept is
centred on the use of trained, lay-persons (grandmoth-
ers) in providing standardised, problem-solving therapy
(psycho-social support intervention) to persons in need
of mental health services. e FB concept is in keep-
ing with the buffering hypothesis which postulates that
increased SS is associated with improved mental health
[14, 15]. e FB has been successfully implemented in
mitigating the effects of social stigma in individuals suf-
fering from CMDs in the Zimbabwean context [44], and
we believe the concept can be successfully integrated into
routine postnatal care.
Conclusion
e prevalence of CMDs was 29.1% and mothers who
received an adequate amount of SS showed optimal
mental health. Being unmarried, lower education sta-
tus, lower income level, and increased maternal age were
associated with poorer maternal mental health. ere is
need for routine surveillance and treatment of CMDs in
women in the postnatal period. More importantly, there
is also need for integration of low-cost, evidenced-based
and task-shifting interventions such as the Friendship
Bench [44] in mitigating the burden of CMDs in this
populace.
Limitations
• Causality cannot be inferred as data were collected
cross-sectionally.
• Purposively selection of study sites and participants
may have introduced selection bias.
• Clinical data used in applying the selection criterion
were self-reported.
• Institution-based participant recruitment may have
precluded selection of community-dwelling mothers
at risk of poor mental health.
Additional les
Additional le1. Frequencies of responses on the MSPSS, N = 340. Table
denotes frequencies of responses on the MSPSS, a 12-item social support
outcome measure. Responses are rated on a five-point Likert scale, rang-
ing from “strongly disagree = 1” to “strongly agree = 5 ”.
Additional le2. Frequencies of responses on the SSQ, N = 340. Table
denotes frequencies of responses on the SSQ, a 14-item, binary common
mental disorders (CMDs) screen. Respondents indicate if they had experi-
enced any of the enlisted symptoms in the last seven days. A yes response
is scored as “one” and no as “zero”, a score ≥ 8 is indicative of risk of CMD.
Additional le3. Variance explained by the model. Table denotes the
variance accounted by the variables and the total model expressing the
relationship between contextual factors, levels of perceived social support
and report of common mental disorders.
Abbreviations
AIDS: acquired immune deficiency syndrome; CFI: Comparative Fit Index;
CMDs: common mental disorders; HIV: human immunodeficiency virus; JREC:
Joint Research and Ethics Committee for the University of Zimbabwe, College
of Health Sciences & Parirenyatwa Group of Hospitals; MSPSS: Multidimen-
sional Scale of Perceived Social Support; PND: postnatal depression; RMSEA:
root mean square error of approximation; SD: standard deviation; SRMR: stand-
ardized root mean square residual; SS: social support; SSQ: Shona Symptom
Questionnaire; TLI: Tucker–Lewis Index.
Authors’ contributions
TK, MC and JMD developed the concept and design of the study. TK collected
the data and drafted the first version of the manuscript. JMD conducted
the data analysis and statistical interpretation, revised the first version of
the manuscript, prepared all prerequisite processes for articles submission,
submitted the manuscript and is the corresponding author. JJ, CT and MC
critically appraised/peer-reviewed and made substantive contributions on the
second to fifth versions of the manuscript in preparation for submission to the
journal. All authors read and approved the final manuscript.
Page 6 of 7
Kasekeetal. BMC Res Notes (2019) 12:110
Author details
1 Department of Rehabilitation, University of Zimbabwe, College of Health
Sciences, P.O Box A178, Avondale, Harare, Zimbabwe. 2 Department of Com-
munity Medicine, University of Zimbabwe, College of Health Sciences, P.O Box
A178, Avondale, Harare, Zimbabwe. 3 Department of Physiotherapy, School
of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwa-
tersrand, Johannesburg, South Africa. 4 School of Health and Rehabilitation
Sciences, Faculty of Health Sciences, University of Cape Town Observatory,
Cape Town 7700, South Africa.
Acknowledgements
We would want to acknowledge participants for their invaluable participa-
tion especially. The data were collected as part of TK’s undergraduate thesis
which JMD supervised her. Appreciation also goes to the AMARI consortium
for various capacity building initiatives which facilitated the writing of the
present manuscript. The manuscript is a product of the manuscript writing
and systematic review workshops facilitated by Dr. Helen Jack (Harvard
University/Kings College London). Further, the manuscript is also a practical
application of the Academic Career Enhancement Series (ACES) program led
by Dr. Christopher Merritt (Kings College London). The senior author utilized
the skills acquired through the ACES program in both thesis supervision and
mentoring of the first author in producing the first draft of the manuscript.
Statistical skills learnt from the data analysis workshops by Dr. Lorna Gibson
and Professor Helen Weiss (London School of Hygiene and Tropical Medicine)
were also fundamental in enhancing the senior authors’ statistical analysis and
interpretation skills.
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
The datasets used and/or analysed during the current study are available from
the corresponding author on reasonable request. The datasets will be availed
onto online repositories once all manuscripts related to the study have been
published online.
Consent for publication
Not applicable as the manuscript does not contain any data from any indi-
vidual person.
Ethics approval and consent to participate
Ethical approval for the study was granted by the City of Harare Health
Department and the Joint Research and Ethics Committee for the University
of Zimbabwe, College of Health Sciences & Parirenyatwa Group of Hospitals
(Ref: JREC/362/17). Participants were treated as autonomous agents and
were requested to sign written consent before participation. Pseudo-names
were used to preserve confidentiality, data were stored securely, and only the
researchers had access to the information gathered, and participants could
voluntarily withdraw from the study at any time without any consequences.
Funding
The MSPSS was adapted, translated and validated into Shona as part of the
senior authors’ Ph.D. work at the University of Cape Town. The work is being
funded by The African Mental Health Research Initiative (AMARI). AMARI is a
consortium of four African universities whose overall goal is to build excel-
lence in leadership, training and science amongst African scholars in mental,
neurological and substance use (MNS) research in Ethiopia, Malawi, South
Africa and Zimbabwe. AMARI, at the University of Zimbabwe College of Health
Sciences (UZCHS), secured funding from the Wellcome Trust through the
Developing Excellence in Leadership and Science (DELTAS) Africa initiative.
The DELTAS Africa Initiative is an independent funding scheme of the African
Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in
Africa (AESA) and supported by the New Partnership for Africa’s Development
Planning and Coordinating Agency (NEPAD Agency) with funding from the
Wellcome Trust [DEL-15-01] and the UK government. The views expressed in
this publication are those of the author(s) and not necessarily those of AAS,
NEPAD Agency, Wellcome Trust, or the UK government. The funding agency
had no role in the design of the study and collection, analysis, interpretation
of data, or in writing the manuscript.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub-
lished maps and institutional affiliations.
Received: 7 November 2018 Accepted: 22 February 2019
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