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POVERTY AND PERCEIVED STRESS IN ZAMBIA
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Poverty and perceived stress: evidence from two unconditional cash transfer programmes in Zambia
[Version accepted for publication in Social Science and Medicine:
http://www.sciencedirect.com/science/article/pii/S0277953617300308]
Lisa Hjelm1
Sudhanshu Handa1,2
Jacobus de Hoop1
Tia Palermo1
on behalf of the Zambia CGP and MCP Evaluation Teams
1 UNICEF Office of Research – Innocenti
Piazza SS. Annunziata, 12,
50122 Florence, Italy
2 Carolina Population Center, University of North Carolina at Chapel Hill
206 West Franklin St., Rm. 208 Chapel Hill, NC 27516, USA
Email addresses:
Lisa Hjelm: lhjelm@unicef.org; Sudhanshu Handa : shanda@unicef.org, shanda@email.unc.edu; Jacobus de Hoop: jdehoop@unicef.org; Tia Palermo: tmpalermo@unicef.org
Corresponding author:
Lisa Hjelm, UNICEF, Eastern and Southern Africa, PO Box 44145-00100 Nairobi, Kenya lhjelm@unicef.org
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Abstract
Introduction: Poverty is a chronic stressor that can lead to poor physical and mental health.
This study examines whether two similar government poverty alleviation programs reduced
the levels of perceived stress and poverty among poor households in Zambia.
Methods: Secondary data from two cluster randomized controlled trials were used to
evaluate the impacts of two unconditional cash transfer programs in Zambia. Participants
were interviewed at baseline and followed over 36 months. Perceived stress among female
caregivers was assessed using the Cohen Perceived Stress Scale (PSS). Poverty indicators
assessed included per capita expenditure, household food security, and (nonproductive) asset
ownership. Fixed effects and ordinary least squares regressions were run, controlling for age,
education, marital status, household demographics, location, and poverty status at baseline.
Results: Cash transfers did not reduce perceived stress but improved economic security (per
capita consumption expenditure, food insecurity, and asset ownership). Among these poverty
indicators, only food insecurity was associated with perceived stress. Age and education
showed no consistent association with stress, whereas death of a household member was
associated with higher stress levels.
Conclusion: In this setting, perceived stress was not reduced by a positive income shock but
was correlated with food insecurity and household deaths, suggesting that food security is an
important stressor in this context. Although the program did reduce food insecurity, the size
of the reduction was not enough to generate a statistically significant change in stress levels.
The measure used in this study appears not to be correlated with characteristics to which it
has been linked in other settings, and thus, further research is needed to examine whether this
widely used perceived stress measure appropriately captures the concept of perceived stress
in this population.
Key words: perceived stress, unconditional cash transfer, food security
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Stress is a determinant of poor mental health, a leading cause of years lived with
disability in high-, middle- and low-income countries (Vos et al., 2015), and it is an important
determinant of overall well-being. Therefore, it is important to measure stress as an outcome
in its own right (Haushofer & Shapiro, 2016; Kling, 2007). Stress and mental health are both
closely linked to poverty; studies from low- and middle-income countries have revealed a
link between poor mental health and socioeconomic status (SES) indicators such as
education, food insecurity, housing, social class, and financial stress (Lund et al., 2010).
Given the adverse effects of poverty on mental health, this study hypothesized that a poverty-
alleviation program (an unconditional cash transfer) would reduce poverty among poor
households in Zambia and subsequently reduce stress.
There are several hypothesized mechanisms through which poverty may influence
mental health, including chronic stress, malnutrition, substance abuse, social exclusion, and
exposure to trauma and violence. Known as the social causation hypothesis, it has been
studied extensively (Johnson et al., 1999; Lund et al., 2011). Further, in what is known as the
social drift hypothesis, people with mental illness are at increased risk of experiencing
poverty through increased health expenditures, reduced productivity, and stigma related to
mental health (Lund et al., 2011). Thus, poverty and poor mental health mutually reinforce
each other (Lorant et al., 2003; Lund et al., 2011). Poverty and low SES may also affect an
individual’s exposure to stress and stressful life events as well as his or her ability to cope
with stress, as fewer social and psychological resources are usually available to overcome
stressful events (Adler et al., 1994; Cohen, 1988; Cohen & Janicki‐Deverts, 2012; Hamad et
al., 2008).
Stress as a mechanism that links poverty and health merits further investigation.
Psychological stress, described as the experience of environmental demands exceeding the
ability to cope with the situation (Lazarus & Folkman, 1984), is associated with a range of
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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physical and mental health states. It has been linked to depressive disorder, depressive
symptoms, cardiovascular disease, and the risk of progressing from HIV infection to AIDS
(Cohen et al., 2007). Experimental studies have shown that acute and chronic stressors can
produce biological stress reactions, including excessive inflammation (McEwen & Seeman,
1999). Over the course of a lifetime, these reactions may contribute to morbidity and
mortality disparities and increased levels of cortisol, particularly for stressors of an
uncontrollable nature (Miller et al., 2007). Poverty-induced chronic stress has also been
hypothesized to accelerate the natural aging of the immune system (referred to as
immunosenescence) (Aiello & Dowd, 2013). Studies have demonstrated that individuals of
lower SES show an increased antibody response to persistent herpes viruses, which may be
due to differential exposure to stress (Aiello & Dowd, 2013) and reduced resources to cope
with it (Kristenson et al., 2004). It is hypothesized that increased stress, caused by a range of
poverty-associated factors, continuously activated stress-related autonomic and
neuroendocrine responses, thus impairing immunity and ultimately leading to poor health
outcomes (Aiello & Dowd, 2013). Maternal perceived stress also has been associated with
low birth weight and poor childhood nutritional status (Dole et al., 2003; Lobel et al., 1992;
Rondó et al., 2013; Torche, 2011).
The majority of studies that examine the relationship between stress, SES (Cohen &
Janicki‐Deverts, 2012; Matthews et al., 2010), and stressful life events are associated with
higher levels of perceived stress (Dowd et al., 2014; van Eck et al., 1998). These variables
have been less studied in sub-Saharan African countries, where food insecurity (Pike & Patil,
2006) and HIV infection (Garcia et al., 2013) are more widespread, which may have
implications for variation in stress levels by SES. A South African study found that perceived
stress was related to subjective social status but not to other socioeconomic indicators, such
as education, employment, and income (Hamad et al., 2008). A Kenyan study among farmers
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demonstrated that elevated levels of cortisol and self-reported stress were induced by the
absence of rain, which caused a negative income shock (Chemin et al., 2013). Another study
found a reduction in self-reported stress due to unconditional cash transfers (a positive
income shock), but no impact on cortisol levels (Haushofer & Shapiro, 2016). A key issue in
all of these studies is the use of measures of stress that have not been validated in sub-
Saharan Africa. Therefore, these measures for stress may not be appropriate in low-income
settings of sub-Saharan Africa.
This study posited that cash transfer programs aimed at improving food security and
smoothing consumption would lead to reduced stress levels in a poor- and food-insecure
setting in sub-Saharan Africa. Cash transfer programs directly aim at poverty alleviation and
not improving outcomes in mental health and related areas. Thus, impacts of the cash transfer
must first work through household-level outcomes—such as food security, economic
security, time use and labor decisions, and general stress levels. Then, the impacts make their
way to individual-level outcomes, such as physical and mental health, perceived stress,
expectations, and outlook.
To date, certain studies in Kenya and Malawi have demonstrated that social cash
transfers have improved mental health in the form of fewer depressive symptoms (as
measured respectively by the Center for Epidemiologic Studies Depression Scale [CES-D]
and the General Health Questionnaire [GHQ-12]). Evidence from Malawi suggests that the
effects of cash transfers on depressive symptoms depend on program design, specifically the
combinations of conditions and transfer amounts. Other studies have reported mixed impacts
on cortisol levels of cash transfer beneficiaries, such as protective impacts among Mexican
children and no impacts among adults in a Kenyan sample (Baird et al., 2013; L. Fernald &
Gunnar, 2009; Haushofer & Shapiro, 2016; Kilburn et al., 2015).
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Current evidence on the relationship between cash transfer programs and perceived
stress is mixed. There are examples of studies that have examined this relationship in Latin
America (Ozer et al., 2011; Schady & Paxson, 2007) and Africa (Haushofer & Shapiro,
2016). In Mexico, participation in the Oportunidades program was associated with lower
depression, and reduced perceived stress [measured by the Perceived Stress Scale (PSS)] was
found to be the mediating factor in women (Ozer et al., 2011). In contrast, in Ecuador,
participation in an unconditional cash transfer program had no significant effect on perceived
stress (measured using a four-item version of the PSS) or on symptoms of depression (Schady
& Paxson, 2007). In Kenya, participation in a cash transfer program reduced perceived stress
(measured by the Cohen PSS) but not cortisol levels in the overall sample. Nonetheless, some
reductions in cortisol were seen among subsamples, such as among female recipients and
among participants who received lump-sum transfers compared to those receiving a monthly
transfer (Haushofer & Shapiro, 2016). On a related note, two additional studies examined the
impacts of loan access and the provision of health care on perceived stress. A Kenyan study
found that health care receipts reduced perceived stress (Chemin et al., 2016). A South
African study found that, among individuals who were initially not offered a small loan, a
second chance to receive the loan increased the levels of perceived stress (Fernald et al.,
2008).
As outlined above, the evidence to date on poverty alleviation and perceived stress is
mixed, and therefore the present study aimed to investigate (1) whether participation in a cash
transfer program reduced poverty-related outcomes and perceived stress and (2) which
individual- and household-level characteristics are associated with higher levels of perceived
stress. To investigate these questions, data from longitudinal impact evaluations of two
government cash transfer programs in Zambia were used. It is important to note that neither
program was designed to address stress, but rather to address food insecurity and extreme
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poverty. Nevertheless, given the theoretical link between poverty and stress, and the fact that
food insecurity is a widespread problem in this population, it is of policy and public health
interest to assess the link between the programs and perceived stress.
Method
Interventions
The Zambia Child Grant Program (CGP) is a government-run unconditional cash
transfer program targeting households with a child under the age of five. The CGP’s
objectives include supplementation of household income, increased enrollment and
attendance in primary school, reduced child morbidity, productive assets, food security, and
improved mortality and nutrition. Districts for program implantation were targeted by the
government because of their high rates of mortality, morbidity, stunting, and wasting among
children aged 0–3 years. Households included in the program receive an amount equivalent to
11 USD per month, which is estimated to be sufficient to cover the cost of one meal per
person per day in an average-sized household. Households “age-out” or graduate from the
program when the index child turns five, although in practice this was not implemented until
after the 36-month evaluation survey was conducted (American Institutes for Research,
2011).
Similar to the Zambia CGP, the Zambia Multiple Category Cash Transfer Program
(MCP) is another government-run unconditional cash transfer program in Zambia, also
implemented by the Ministry of Community Development, Mother and Child Health. The
objectives of the MCP are to assist the most vulnerable households in the society, allowing
them to meet their basic needs related to health, education, food, and shelter. The program
targets households that fall into any of the following categories: female headed and keeping
orphans, having a disabled member, headed by an elderly and keeping orphans, or special
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cases of critically vulnerable households that are not included in any of the aforementioned
categories (American Institutes for Research, 2012).
Sample data
This study used secondary data that were collected as part of the impact evaluations of
the CGP and the MCP. These impact evaluations were randomized controlled trials, designed
and implemented by The American Institutes for Research and the University of North
Carolina at Chapel Hill under contract to UNICEF-Zambia.
The CGP impact evaluation comprised 2,515 households at baseline from 90
communities (randomized into treatment and control arms) in three districts – Kaputa,
Kalabo, and Shang’ombo – for a total evaluation sample size of 14,565 individuals. Baseline
data were collected in December 2010, and follow-up data were collected in September and
October 2012 (24 months), June and July 2013 (30 months), and September and October
2013 (36 months). The MCP impact evaluation took place in 92 communities (randomized to
treatment and control arms) within two districts, Luwingu and Serenje. MCP baseline data,
including 3,078 households and 15,630 individuals, were collected in November and
December 2011, and follow-up data were collected in November and December 2013 (24
months) and November and December 2014 (36 months).
In the subsample for analysis in the present study, data were used from the
observations of female caregivers of children (main household survey respondents). These
caregivers were observed at baseline and 36 months for the MCP and at baseline, 30 months,
and 36 months for the CGP. The official evaluation reports demonstrated balance at baseline
(indicating successful randomization of the treatment and control arms) and no evidence of
selective attrition between study arms (American Institutes for Research, 2011, 2012). Data
collections and analyses plans went through ethical review at the American Institutes for
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Research in Washington, DC, and at the University of Zambia Ethical Review Committee.
Informed consent was obtained from all study participants.
Measures
This study used the PSS to measure psychological stress. The PSS was developed on
the basis of the concept of stress as an interaction between environmental demands and the
individual’s capacity to cope (Cohen et al., 1983). Originally developed with 14 items, its
creators later refined it to 10 items (the PSS10) of which 6 are negatively phrased and 4 are
positively phrased (Cohen, 1988). These items consider the degree to which individuals
experience their lives as unpredictable, uncontrollable, and overloading (Cohen et al., 1983).
This scale is one of the most frequently used measures of perceived stress and has been
validated in many countries around the world; it is increasingly being used in sub-Saharan
Africa (e.g., Garcia et al., 2013; Hamad et al., 2008; Lemma et al., 2012), but to current
knowledge, it has never been validated there. The PSS has been associated with depressive
symptomatology in a number of Western countries using the original English language
questionnaire (Cohen et al., 1983; Eisenbarth, 2012; Hewitt et al., 1992) and in other regions
and languages (e.g., Andreou et al., 2011; Chaaya et al., 2010; Wang et al., 2011).
Consistent with previous research, principal component analysis resulted in two
factors in this study’s samples, one consisting of the negatively worded items and the other
consisting of the positively worded items (Cohen, 1988). However, the two subscales were
not closely correlated. The “negative” subscale showed more variation in relation to
happiness and optimism compared to the “positive” subscale, and the “positive” subscale did
not show consistent associations. Thus, this study concluded that the positively worded items
did not perform well in this setting, and a consolidated stress scale including both positively
and negatively worded items would not be suitable as a single measure of perceived stress in
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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these two samples. This study therefore included only the six negatively worded PSS items.
The questions included in the final scale were:
In the last 4 weeks, how often have you been upset because of something that
happened unexpectedly? In the last 4 weeks, how often have you felt that you were
unable to control the important things in life? In the last 4 weeks, how often have you
felt nervous and “stressed”? In the last 4 weeks, how often have you found that you
could not cope with all things that you had to do? In the last 4 weeks, how often have
you been angered because of things that were outside of your control? In the last 4
weeks, how often have you felt difficulties were piling up so high that you could not
overcome them?
Likert-type responses ranged from 0 (never) to 4 (very often/always). The scale was
constructed by adding the total score from each question resulting in a scale ranging from 0 to
24. Cronbach’s α was 0.84 for the CGP and 0.83 for the MCP sample, indicating the high
internal reliability in each sample. For MCP, 3% of the analysis had missing values for the
PSS, and 6% for CGP. There was no systematic difference in treatment arm, age, education,
or marital status between women who responded and those with missing values. Due to their
relatively small number, these observations were dropped from the analysis.
Because this study hypothesized that cash transfers could alleviate stress through the
poverty pathway, it also examined whether the program affected the following poverty-
related outcomes: household consumption expenditures, food security, and the number of
nonproductive assets owned. Food security was measured using the previously validated
(Knueppel et al., 2010; Maes et al., 2009) Household Food Security Access Scale (HFIAS)
(Coates et al., 2007). The scale consists of nine items capturing different severities of food
security, from worrying about not having enough food to not eating at all because of lack of
food. The questions referred to the past 4 weeks. Severe food insecurity was calculated based
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on the occurrence of the more severe experiences of food insecurity included in the HFIAS
questionnaire, for example, if there was no food to eat of any kind because of a lack of
resources.
Monthly consumption expenditure per capita in Zambia kwacha (ZMW) was
calculated using an expenditure module, which was adopted from the Zambian Living
Conditions Monitoring Survey, covering a broad range of expenditure categories and
including more than 200 items. At follow-up, expenditures were deflated to baseline year
ZMW values, 2010 for CGP and 2011 for MCP.
The asset ownership indicator is the sum of nonproductive assets owned from a list of
10 assets (clock, watch, mobile phone, DVD, television, radio, sofa, table, mattress, and bed)
in the CGP and 7 assets in the MCP (clock, watch, mobile phone, radio, sofa, table, and
mattress).
Covariates
Individual-level control variables included age of the respondent, whether the
respondent had ever attended school – and subsequently – highest grade attained in school;
and whether the respondent was married, never married, divorced, or widowed. Control
variables at household level included the total number of household members, number of
household members of different age groups (0–5, 6–12, 13–18, 19–35, 36–55, 56–69, and
70+ years), and the district where the household was located. It also included the poverty
status at baseline in terms of food insecurity, log of per capita expenditures, and asset
ownership (described above). To measure stressful life events, we examined any death in the
household (recall period since last follow-up survey).
Statistical analyses
This study first examined sample characteristics, including descriptive statistics and
covariates for balance between treatment and control samples at baseline; then two sets of
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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multivariate analyses were performed. In the first set of multivariate analyses, we
investigated treatment effects on perceived stress and poverty-related indicators using
ordinary least square (OLS) regressions. These analyses were conducted using cross-sections
from the latest follow-up waves at which perceived stress data were collected (36-months
follow-up). To estimate program impacts, regressions with a treatment indicator (1=
treatment, 0=otherwise) were run. The covariates listed above were controlled to improve the
precision of the estimates. Additionally, regressions without controls were run, and it was
concluded that adding controls did not significantly change the results. This study used
baseline values of control variables because the program may have affected them, and thus,
using contemporaneous values may have underestimated the treatment effect on outcomes of
interest. Control variables with missing values were replaced with −1, and then an indicator
(+1) variable was added (0=otherwise) to control for missing information (which is why
control variables in Table 1 may have fewer observations than regressions in Tables 2 and 3).
To estimate treatment impacts, these analyses relied on the successful randomization of the
program, which created statistically equivalent treatment and control groups. As there was no
pretreatment measure of the key outcome indicator, the estimated treatment effect assumes
that this measure was balanced at baseline, which is consistent with the results of the balance
tests reported in Table 1 over a range of outcomes.
In the second set of analyses, this study examined determinants of perceived stress by
estimating associations between perceived stress and household- and individual-level
characteristics using OLS regressions on the cross-sectional control samples at 36 months.
Treatment individuals in this latter analysis were excluded as the program may have
mitigated some of the risk factors for stress in the treatment arm. As a robustness check for
the determinants of stress analysis, individual fixed-effects OLS regressions were run using
observations from the CGP control sample at 30 months and 36 months. As these regressions
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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control for unobserved characteristics, which may simultaneously affect both risk factors and
perceived stress, they may reduce any remaining bias in the estimates. All standard errors for
clustering at the community level were adjusted (the level of program randomization). The
data were analyzed using Stata Version 14.
Results
Of the 2,515 households included in the CGP at baseline, 2,273 had a female
caregiver who was observed at baseline and had completed the PSS questionnaire at 30 and
36 months. In the MCP, of the 3,077 households included at baseline, 2,490 households had a
female caregiver who was observed at baseline and had completed the PSS questionnaire at
36 months.
Table 1 describes the covariates and the poverty-related outcome variables at baseline,
and examines the balance between the treatment and control groups of the two samples at
baseline. Treatment and control arms were balanced (i.e., there were no statistically
significant differences between treatment and control arms) at baseline for both samples.
Although the average age for women interviewed in the CGP households was approximately
30 years, women in MCP households were considerably older with an average age of 52
years. The poverty-related outcome variables illustrate the deprived background of the
households benefitting from these programs. Per capita monthly expenditure at baseline was
40 ZMW for households in the CGP and 49 ZMW for households in the MCP, roughly
equivalent to 8 USD (or 26 cents per person per day) for CGP households and 10 USD (or 33
cents per person per day) for MCP households. Approximately 90% of the CGP households
and 81% of the MCP households were severely food insecure at baseline.
[Insert Table 1 about here]
Within the individual items making up the PSS, among the women in the CGP and
MCP control groups, respectively 6% and 22% had been upset because something happened
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unexpectedly; 8% and 19% had felt that they were unable to control the important things in
life; 11% and 23% had felt nervous and stressed;12% and 21% had found that they could not
cope with all things that they had to do; 12% and 21% had been angered because things were
outside their control; and 18% and 27% had felt that difficulties were piling up so high that
they could not overcome them fairly often or very often/always in the 4 weeks preceding the
survey.
Table 2 shows the program impacts on perceived stress and poverty-related indicators
for the CGP in Panel A and MCP in Panel B. The results indicate that the program had no
statistically significant impact on perceived stress (columns 1 and 2). However, the program
was successful in reducing poverty-related outcomes. It increased the monthly per capita
expenditures by 10 ZMW (17 ZMW in the MCP; column 2), an increase of 20% (28% in
MCP). It also reduced household food insecurity by three points (0.5 SD) on the HFIAS
[three points (0.6 SD) in the MCP; column 3] and increased nonproductive assets by 0.7
items (0.4 in the MCP; column 4) on average.
[Insert Table 2 about here]
Table 3 presents the results examining the determinants of perceived stress using only
observations from the control groups. In the OLS regressions (columns 1 and 3), it was found
that the only covariate associated with perceived stress was household food insecurity, which
was associated with stress levels that were 0.15 points higher in the CGP and 0.27 points
higher in the MCP on average. After controlling for unobserved factors in the fixed effects
model in the CGP, this study found that death in the household was also associated with
stress levels that were 1.63 points higher on average (column 2). Age, educational attainment,
household consumption expenditures, and assets were not associated with stress levels in
these samples.
[Insert Table 3 about here]
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Discussion
This study examined whether participation in an unconditional cash transfer program
reduced perceived stress. Although the program was successful in reducing poverty as
measured by three different household-level indicators, this study found no program impacts
on perceived stress levels. These findings are similar to those from Ecuador, where
participation in an unconditional cash transfer program had no effect on perceived stress
(Schady & Paxson, 2007). However, the findings of this current study contrast with
quantitative findings from Kenya and Mexico, which found that cash transfers reduced
perceived stress (as measured by the PSS) (Haushofer & Shapiro, 2016; Ozer et al., 2011).
When this study examined correlates of perceived stress, only food insecurity and
household deaths were related to higher levels of stress, which suggests that the experience of
not having enough food in the household is a key source of stress compared to other aspects
of poverty that were examined. High levels of food insecurity are a persistent challenge in
sub-Saharan Africa (FAO et al., 2015). In sub-Saharan African rural settings, food insecurity
may be a more prominent source of insecurity than in other locations, particularly in
subsistence farming settings with distinct seasonal variations in the accessibility of food
(Hadley & Patil, 2008). The insecurity of not knowing where the next meal will come from,
having to deprioritize other necessities, and the shame of not having enough food for the
children, causes stress among those that are living in food insecurity (Hadley et al., 2012).
Hunger and food insecurity have been identified as important stressors in sub-Saharan Africa
(Pike & Patil, 2006), and the experience of food insecurity as a stressful event raises the
levels of perceived stress (Addo et al., 2011). The stress of food insecurity potentially
explains the link between household food insufficiency and increased risk for depression that
has been found in a number of studies in sub-Saharan Africa (Hadley et al., 2008; Maes et al.,
2010; Palermo et al., 2013; Tsai et al., 2016), particularly in Zambia (Cole & Tembo, 2011).
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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There are several possible explanations regarding why this study did not find an
association between stress and consumption expenditures, asset ownership, or cash transfer
receipt. One is that relative poverty or the perceived SES could be more important in
determining stress levels than absolute levels of poverty (measured by expenditures and asset
ownership), and this is supported by research done in South Africa (Hamad et al., 2008).
Several studies from high-income countries have shown that relative experience of
deprivation can be a source of stress and cause ill health (Adler et al., 1994; Jennifer Beam
Dowd et al., 2008; Schulz et al., 2012). The possibility that the program did affect perceived
social status remains; however, our study did not measure this outcome. The measures of
poverty included in this study are in more absolute terms, and thus do not reflect a person’s
subjective perception of their rank in society, which may be a larger comparative driver of
stress.
A second possible explanation could be that the grant amount was not sufficient to
affect stress levels. The cash may work its way along the pathway from poverty, which it did
affect, but may not have been enough to continue along the pathway to affect stress.
Considering the effect sizes, it can be concluded that the treatment effect on food insecurity is
large, with a 2.9-point reduction on the food insecurity scale for CGP beneficiaries. However,
although the association between food security and perceived stress was statistically
significant, the coefficient was small. In the CGP, a one-point decrease on the food insecurity
scale resulted in a 0.12-point reduction on the PSS. Consequently, the hypothesized treatment
effect on perceived stress through reduced food insecurity would result in a 0.35-point (2.9
0.12) or 0.08-SD reduction in perceived stress for CGP beneficiaries. The corresponding
figure for the MCP would be a 0.8-point or 0.17 SD reduction in perceived stress, which is
slightly higher but still not large enough to be detected in this study sample. Beyond the size
of the grant, other aspects of program implementation such as predictability of payment could
POVERTY AND PERCEIVED STRESS IN ZAMBIA
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also affect stress. Yet, in both the programs, payments were made regularly and on-time;
therefore, this is unlikely to explain the lack of impacts on PSS.
A third theory is that the PSS10, which was first developed in a Western setting, does
not adequately capture stress in a poor, rural setting in sub-Saharan Africa. It has been argued
that the concept of “stress” may not be used and understood the same way in all cultural
contexts (Pike & Patil, 2006) and that a context-specific stress scale based on local conditions
and expectations may better capture the experience of stress (Ice et al., 2012). The possible
inadequacy of the PSS to capture stress in this context could also explain why age and
education, which are factors that are typically associated with levels of perceived stress in
other settings (Cohen & Janicki‐Deverts, 2012; Dowd et al., 2014; Remor, 2006), showed no
consistent findings in this study’s samples. Although there was no association between age
and perceived stress in these samples, the relatively older women in the MCP households
report more stress. This finding may be a function of stress increasing with age or with the
targeting criteria for the MCP, which targets households in potentially demanding situations,
such as caring for orphans and disabled household members. In contrast, CGP beneficiaries
are targeted based on the sole criteria of having a child under the age of five in the household
(in very poor geographic areas).
Nonetheless, our study did find that one measured stressful life event—a death in the
family—was associated with higher perceived stress, which is confirmed by findings
elsewhere (Cohen et al., 1983). Thus, the PSS10 may be better able to pick up stressful life
events in this setting but is less sensitive to chronic daily stress. Chronic daily stress is a key
hypothesized mediator for poverty alleviation programs, and it is therefore important to
measure in impact evaluations of cash transfer programs (Haushofer & Shapiro, 2016; Kling,
2007).
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Finally, the divergence between findings on food insecurity and PSS may be
explained by the fact that HFIAS includes items that capture both material outcomes (having
enough to eat) and mental outcomes (worrying about food), and the material outcomes may
drive the impact on the overall scale. To explore this hypothesis, this study estimated
program impacts on each individual item in the scale separately and found significant impacts
on each item (results not displayed). The key difference, of course, is that the mental items in
the HFIAS relate specifically to food, whereas they are more general in the PSS. This
underscores the idea that food insecurity is the critical dimension of well-being in this
population.
Limitations
There are some limitations to this study. Although the PSS is widely used and
validated globally, it has never, to our knowledge, been validated in a sub-Saharan African
setting. Further, psychometric problems mean that this study was not able to use all 10 items
on the PSS10 scale; instead, this study used a subset of six questions because the positively
worded question items performed poorly in this setting.
The key outcome used in this paper was only collected at follow-up. Thus, causal
inference relies on the assumption of baseline equivalence in the mean value of the stress
indicator across study arms. This limitation is mitigated by the fact that in both studies
assignment to study arm was done randomly, and baseline equivalence is established among a
range of other indicators including a key determinant of stress—household food security.
A final limitation concerns the potential generalizability of these findings to other
rural populations in sub-Saharan Africa. The two cash transfer programs targeted ultra-poor
households with unique demographic profiles, households with a pre-school child in the
CGP, and households with a disabled member or an elderly or female head caring for orphans
in the MCP. The combination of absolute poverty and demographic vulnerability may result
POVERTY AND PERCEIVED STRESS IN ZAMBIA
19
in unique stressors which may not be relevant for other types of poor households in rural sub-
Saharan Africa.
Future Studies
The findings of this study can explain how different aspects of poverty may
differentially affect mental health in low-income countries, with stress as a potential pathway
between poverty and mental health. Future studies, particularly in sub-Saharan Africa and
specifically Zambia, should investigate the concept of stress and how poverty relates to
different measures of stress. The inconsistency in findings of the present study compared to
those of previous studies indicates that the stress scale is inadequately measuring stress in this
context. The PSS should be validated in a sub-Saharan African setting, and a more regionally
appropriate scale should be developed.
Acknowledgements
The CGP and MCP impact evaluations were commissioned by the Government of Zambia (GRZ)
through the Ministry of Community Development, Mother and Child Health to the American
Institutes of Research (AIR) and the University of North Carolina at Chapel Hill (UNC) and funded
by a consortium of donors including DFID, UNICEF, Irish Aid, and the Government of Finland.
Palermo, Handa, and Hjelm received additional funding from the Swedish International Development
Cooperation and de Hoop received additional funding from the US Department of Labor to the
UNICEF Office of Research - Innocenti for analysis of the data and drafting of the manuscript.
The members of the CGP evaluation team, listed by affiliation and then alphabetically within
affiliation are:
Principal Investigators: David Seidenfeld (AIR) and Sudhanshu Handa (UNC); AIR: Juan Bonilla,
Rosa Castro Zarzur, Leah Prencipe, Dan Sherman, David Seidenfeld; UNICEF-Zambia: Charlotte
Harland Scott, Paul Quarles van Ufford; Government of Zambia: Vandras Luywa, Stanfield Michelo,
Manzunzo Zulu; DFID-Zambia: Kelley Toole; Palm Associates: Alefa Banda, Chiluba Goma, Liseteli
POVERTY AND PERCEIVED STRESS IN ZAMBIA
20
Ndiyoi, Gelson Tembo, NathanTembo); UNC: Sudhanshu Handa; UNICEF Office of Research –
Innocenti: Sudhanshu Handa, Tia Palermo, Amber Peterman, Leah Prencipe.
The members of the MCP evaluation team, listed by affiliation and then alphabetically within
affiliation are:
Principal Investigators: David Seidenfeld (AIR) and Sudhanshu Handa (UNC); AIR: Juan Bonilla,
Alvaro Ballarin Cabrera, Thomas De Hoop, Gilbert Kiggundu, Nisha Rai, Hannah Reeves, Joshua
Sennett, Dan Sherman, Jonathan Sokoll, Amy Todd, Rosa Castro Zarzur; Palm Associates: Alefa
Banda, Liseteli Ndiyoi, Nathan Tembo; UNC: Sudhanshu Handa; UNICEF Office of Research -
Innocenti: Tia Palermo, Amber Peterman, Leah Prencipe
POVERTY AND PERCEIVED STRESS IN ZAMBIA
21
References
Addo, A.A., Marquis, G.S., Lartey, A.A., Pérez‐Escamilla, R., Mazur, R.E., & Harding, K.B.
(2011). Food insecurity and perceived stress but not HIV infection are independently
associated with lower energy intakes among lactating Ghanaian women. Maternal &
Child Nutrition, 7, 80-91.
Adler, N.E., Boyce, T., Chesney, M.A., Cohen, S., Folkman, S., Kahn, R.L., et al. (1994).
SES and health: the challenge of the gradient. American Psychologist, 49, 15-23.
Aiello, A.E., & Dowd, J.B. (2013). Socio-economic Status and Immunosenescence. In Jos A.
Bosch, J.A., Anna C. Phillips, A.C. & Lord, J.M (Eds.), Immunosenescence, New
York, Springer, pp. 145-157.
American Institutes for Research. (2011). Zambia’s Child Grant Program: Baseline Report.
Washington, DC: American Institutes for Research.
American Institutes for Research. (2012). Zambia’s Multiple Category Cash Transfer
Program: Baseline Report. Washington, DC: American Institutes for Research.
Andreou, E., Alexopoulos, E.C., Lionis, C., Varvogli, L., Gnardellis, C., Chrousos, G.P., et
al. (2011). PSS: reliability and validity study in Greece. International Journal of
Environmental Research and Public Health, 8, 3,287-3,298.
Baird, S., De Hoop, J., & Özler, B. (2013). Income shocks and adolescent mental health.
Journal of Human Resources, 48, 370-403.
Chaaya, M., Osman, H., Naassan, G., & Mahfoud, Z. (2010). Validation of the Arabic
version of the Cohen PSS (PSS-10) among pregnant and postpartum women. BMC
Psychiatry, 10, 111.
Chemin, M., De Laat, J., & Haushofer, J. (2013). Negative rainfall shocks increase levels of
the stress hormone cortisol among poor farmers in Kenya. Available at SSRN
POVERTY AND PERCEIVED STRESS IN ZAMBIA
22
2294171: http://ssrn.com/abstract=2294171 or
http://dx.doi.org/10.2139/ssrn.2294171.
Chemin, M., Haushofer, J., & Jang, C. (2016). Health Insurance Reduces Stress: Evidence
from a Randomized Experiment in Kenya. Available at
http://econ.as.nyu.edu/docs/IO/42071/Chemin_Haushofer_Jang_Insurance_2016.03.1
0.pdf
Coates, J., Swindale, A., & Bilinsky, P. (2007). Household Food Insecurity Access Scale
(HFIAS) for measurement of food access: indicator guide. Washington, DC: Food and
Nutrition Technical Assistance Project, Academy for Educational Development.
Cohen, S. (1988). Perceived stress in a probability sample of the United States. In S.
Spacapan, & S. Oskamp (Eds.), The Social Psychology of Health. Newbury Park, CA,
Sage, pp 31-67.
Cohen, S., Janicki-Deverts, D., & Miller, G.E. (2007). Psychological stress and disease.
JAMA, 298, 1,685-1,687.
Cohen, S., & Janicki‐Deverts, D. (2012). Who's stressed? Distributions of psychological
stress in the United States in probability samples from 1983, 2006, and 20091.
Journal of Applied Social Psychology, 42, 1,320-1,334.
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress.
Journal of Health and Social Behavior, 24, 385-396.
Cole, S.M., & Tembo, G. (2011). The effect of food insecurity on mental health: panel
evidence from rural Zambia. Social Science & Medicine, 73, 1,071-1,079.
Cole, S.R. (1999). Assessment of differential item functioning in the PSS-10. Journal of
Epidemiology and Community Health, 53, 319-320.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
23
Dole, N., Savitz, D.A., Hertz-Picciotto, I., Siega-Riz, A.M., McMahon, M.J., & Buekens, P.
(2003). Maternal stress and preterm birth. American Journal of Epidemiology, 157,
14-24.
Dowd, J.B., Haan, M.N., Blythe, L., Moore, K., & Aiello, A.E. (2008). Socioeconomic
gradients in immune response to latent infection. American Journal of Epidemiology,
167, 112-120.
Dowd, J.B., Palermo, T., Chyu, L., Adam, E., & McDade, T.W. (2014). Race/ethnic and
socioeconomic differences in stress and immune function in The National
Longitudinal Study of Adolescent Health. Social Science & Medicine, 115, 49-55.
Eisenbarth, C. (2012). Does self-esteem moderate the relations among perceived stress,
coping, and depression? College Student Journal, 46, 149-157.
FAO, IFAD, & WFP. (2015). The State of Food Insecurity in the World 2015. Meeting the
2015 international hunger targets: taking stock of uneven progress. Rome: FAO.
Fernald, L., & Gunnar, M.R. (2009). Effects of a poverty-alleviation intervention on salivary
cortisol in very low-income children. Social Science & Medicine, 68, 2,180-2,189.
Fernald, L.C., Hamad, R., Karlan, D., Ozer, E.J., & Zinman, J. (2008). Small individual loans
and mental health: a randomized controlled trial among South African adults. BMC
Public Health, 8, 409.
Garcia, J., Hromi-Fiedler, A., Mazur, R.E., Marquis, G., Sellen, D., Lartey, A., et al. (2013).
Persistent household food insecurity, HIV, and maternal stress in peri-urban Ghana.
BMC Public Health, 13, 215.
Hadley, C., & Patil, C.L. (2008). Seasonal changes in household food insecurity and
symptoms of anxiety and depression. American Journal of Physical Anthropology,
135, 225-232.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
24
Hadley, C., Stevenson, E.G.J., Tadesse, Y., & Belachew, T. (2012). Rapidly rising food
prices and the experience of food insecurity in urban Ethiopia: impacts on health and
well-being. Social Science & Medicine, 75, 2,412-2,419.
Hadley, C., Tegegn, A., Tessema, F., Cowan, J., Asefa, M., & Galea, S. (2008). Food
insecurity, stressful life events and symptoms of anxiety and depression in east
Africa: evidence from the Gilgel Gibe growth and development study. Journal of
Epidemiology and Community Health, 62, 980-986.
Hamad, R., Fernald, L.C., Karlan, D.S., & Zinman, J. (2008). Social and economic correlates
of depressive symptoms and perceived stress in South African adults. Journal
Epidemiology and Community Health, 62, 538-544.
Haushofer, J., & Shapiro, J. (2016). The short-term impact of unconditional cash trasnfers to
the poor Quarterly Journal of Economics, Forthcoming.
Hewitt, P.L., Flett, G.L., & Mosher, S.W. (1992). The PSS: Factor structure and relation to
depression symptoms in a psychiatric sample. Journal of Psychopathology and
Behavioral Assessment, 14, 247-257.
Ice, G.H., Sadruddin, A.F., Vagedes, A., Yogo, J., & Juma, E. (2012). Stress associated with
caregiving: An examination of the stress process model among Kenyan Luo elders.
Social Science & Medicine, 74, 2,020-2,027.
Johnson, J.G., Cohen, P., Dohrenwend, B.P., Link, B.G., & Brook, J.S. (1999). A
longitudinal investigation of social causation and social selection processes involved
in the association between SES and psychiatric disorders. Journal of Abnormal
Psychology, 108, 490.
Kilburn, K., Thirumurthy, H., Halpern, C.T., Pettifor, A., & Handa, S. (2015). Effects of a
Large-Scale Unconditional Cash Transfer Program on Mental Health Outcomes of
Young People in Kenya. Journal of Adolescent Health, 58, 223-229.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
25
Kling, J.R. (2007). Methodological frontiers of public finance field experiments. Cambridge,
MA: National Bureau of Economic Research.
Knueppel, D., Demment, M., & Kaiser, L. (2010). Validation of the household food
insecurity access scale in rural Tanzania. Public Health Nutrition, 13, 360-367.
Kristenson, M., Eriksen, H.R., Sluiter, J.K., Starke, D., & Ursin, H. (2004). Psychobiological
mechanisms of socioeconomic differences in health. Social Science & Medicine, 58,
1,511-1,522.
Lazarus, R.S., & Folkman, S. (1984). Stress, appraisal, and coping: Springer publishing
company.
Lemma, S., Gelaye, B., Berhane, Y., Worku, A., & Williams, M.A. (2012). Sleep quality and
its psychological correlates among university students in Ethiopia: a cross-sectional
study. BMC Psychiatry, 12, 237.
Leung, D.Y., Lam, T.-h., & Chan, S.S. (2010). Three versions of PSS: validation in a sample
of Chinese cardiac patients who smoke. BMC Public Health, 10, 513.
Lobel, M., Dunkel-Schetter, C., & Scrimshaw, S.C. (1992). Prenatal maternal stress and
prematurity: a prospective study of socioeconomically disadvantaged women. Health
Psychology, 11, 32-40.
Lorant, V., Deliège, D., Eaton, W., Robert, A., Philippot, P., & Ansseau, M. (2003).
Socioeconomic inequalities in depression: a meta-analysis. American Journal of
Epidemiology, 157, 98-112.
Lund, C., Breen, A., Flisher, A.J., Kakuma, R., Corrigall, J., Joska, J.A., et al. (2010).
Poverty and common mental disorders in low and middle income countries: a
systematic review. Social Science & Medicine, 71, 517-528.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
26
Lund, C., De Silva, M., Plagerson, S., Cooper, S., Chisholm, D., Das, J., et al. (2011).
Poverty and mental disorders: breaking the cycle in low-income and middle-income
countries. The Lancet, 378, 1,502-1,514.
Maes, K.C., Hadley, C., Tesfaye, F., & Shifferaw, S. (2010). Food insecurity and mental
health: surprising trends among community health volunteers in Addis Ababa,
Ethiopia during the 2008 food crisis. Social Science & Medicine, 70, 1,450-1,457.
Maes, K.C., Hadley, C., Tesfaye, F., Shifferaw, S., & Tesfaye, Y.A. (2009). Food insecurity
among volunteer AIDS caregivers in Addis Ababa, Ethiopia was highly prevalent but
buffered from the 2008 food crisis. The Journal of Nutrition, 139, 1,758-1,764.
Matthews, K.A., Gallo, L.C., & Taylor, S.E. (2010). Are psychosocial factors mediators of
SES and health connections? Annals of the New York Academy of Sciences, 1186,
146-173.
McEwen, B.S., & Seeman, T. (1999). Protective and damaging effects of mediators of stress:
elaborating and testing the concepts of allostasis and allostatic load. Annals of the
New York Academy of Sciences, 896, 30-47.
Miller, G.E., Chen, E., & Zhou, E.S. (2007). If it goes up, must it come down? Chronic stress
and the hypothalamic-pituitary-adrenocortical axis in humans. Psychological Bulletin,
133, 25-45.
Mimura, C., & Griffiths, P. (2004). A Japanese version of the PSS: translation and
preliminary test. International Journal of Nursing Studies, 41, 379-385.
Ozer, E.J., Fernald, L.C., Weber, A., Flynn, E.P., & VanderWeele, T.J. (2011). Does
alleviating poverty affect mothers’ depressive symptoms? A quasi-experimental
investigation of Mexico’s Oportunidades program. International Journal of
Epidemiology, 40, 1,565-1,576.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
27
Palermo, T., Rawat, R., Weiser, S.D., & Kadiyala, S. (2013). Food access and diet quality are
associated with quality of life outcomes among HIV-infected individuals in Uganda.
PLOS ONE, 8, e62353.
Pike, I.L., & Patil, C.L. (2006). Understanding women’s burdens: preliminary findings on
psychosocial health among Datoga and Iraqw women of northern Tanzania. Culture,
Medicine and Psychiatry, 30, 299-330.
Ramírez, M.T.G., & Hernández, R.L. (2007). Factor structure of the PSS (PSS) in a sample
from Mexico. The Spanish journal of psychology, 10, 199-206.
Reis, R.S., Hino, A.A.F., & Añez, C.R.R. (2010). PSS reliability and validity study in Brazil.
Journal of health psychology, 15, 107-114.
Remor, E. (2006). Psychometric properties of a European Spanish version of the PSS (PSS).
The Spanish journal of psychology, 9, 86-93.
Rondó, P., Rezende, G., Lemos, J., & Pereira, J. (2013). Maternal stress and distress and
child nutritional status. European journal of clinical nutrition, 67, 348-352.
Schady, N., & Paxson, C.H. (2007). Does money matter? The effects of cash transfers on
child health and development in rural Ecuador. World Bank Policy Research Working
Paper No 4226.
Schulz, A.J., Mentz, G., Lachance, L., Johnson, J., Gaines, C., & Israel, B.A. (2012).
Associations between SES and allostatic load: effects of neighborhood poverty and
tests of mediating pathways. American Journal of Public Health, 102, 1706-1714.
Torche, F. (2011). The effect of maternal stress on birth outcomes: exploiting a natural
experiment. Demography, 48, 1,473-1,491.
Tsai, A.C., Tomlinson, M., Comulada, W.S., & Rotheram-Borus, M.J. (2016). Food
insufficiency, depression, and the modifying role of social support: evidence from a
POVERTY AND PERCEIVED STRESS IN ZAMBIA
28
population-based, prospective cohort of pregnant women in peri-urban South Africa.
Social Science & Medicine, 151, 69-77.
van Eck, M., Nicolson, N.A., & Berkhof, J. (1998). Effects of stressful daily events on mood
states: relationship to global perceived stress. Journal of personality and social
psychology, 75, 1,572-1,585.
Vos, T., Barber, R.M., Bell, B., Bertozzi-Villa, A., Biryukov, S., Bolliger, I., et al. (2015).
Global, regional, and national incidence, prevalence, and years lived with disability
for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a
systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 386,
743-800.
Wang, Z., Chen, J., Boyd, J.E., Zhang, H., Jia, X., Qiu, J., et al. (2011). Psychometric
properties of the Chinese version of the PSS in policewomen. PLOS ONE, 6, e28610.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
29
Table 1. Household characteristics of the Zambia Child Grant Programme (CGP) and Multiple Category Cash Transfer Programme (MCP) samples, baseline
Panel A: CGP N All Control
(proportion /mean)
Treatment (proportion
/mean) P-value
Characteristics of women
Age 2,272 29.79 29.64 29.95 0.65 Ever attended school 2,271 0.71 0.70 0.73 0.40 Highest grade completed 2,261 3.93 3.70 4.17 0.09 Married 2,266 0.73 0.72 0.74 0.73 Never married 2,266 0.10 0.10 0.11 0.78 Divorced 2,266 0.10 0.11 0.09 0.10 Widowed 2,266 0.06 0.06 0.07 0.87 Household demographics
Household size 2,273 5.71 5.65 5.77 0.51 Number of people ages 0 - 5 2,273 1.91 1.92 1.90 0.68 Number of people ages 6 - 12 2,273 1.27 1.27 1.27 1.00 Number of people ages 13 - 18 2,273 0.56 0.53 0.60 0.15 Number of people ages 19 - 55 2,273 1.87 1.83 1.90 0.18 Number of people ages 56 or older 2,273 0.09 0.10 0.09 0.95 Material well-being
Household food insecurity access scale (HFIAS) (0-24)a
2,235 15.23 15.4 15.05 0.55
Severely food insecure households 2,243 0.90 0.90 0.90 0.90 Total household expenditure per
person in the household 2,271 39.82 38.87 40.79 0.46
Assets owned (0-10) 2,273 0.82 0.73 0.92 0.12 Minimum N 2235 1127 1106
Panel B: MCP
Characteristics of women
Age 2,490 51.62 51.26 51.98 0.50 Ever attended school 2,481 0.61 0.63 0.60 0.42 Highest grade completed 2,458 3.03 3.09 2.98 0.64 Married 2,474 0.29 0.30 0.29 0.83 Never married 2,474 0.05 0.06 0.04 0.01 Divorced 2,474 0.14 0.14 0.14 0.96 Widowed 2,474 0.51 0.50 0.53 0.37 Household demographics
Household size 2,490 5.16 5.18 5.14 0.84 Number of people ages 0 - 5 2,490 0.75 0.73 0.77 0.51 Number of people ages 6 - 12 2,490 1.33 1.28 1.38 0.19 Number of people ages 13 - 18 2,490 0.98 1.03 0.94 0.11 Number of people ages 19 - 55 2,490 1.38 1.41 1.34 0.46 Number of people ages 56 or older 2,490 0.72 0.74 0.71 0.55 Material well-being
Household food insecurity access scale (HFIAS) (0-24)a
2,431 14.68 14.61 14.75 0.76
Severely food insecure households 2,459 0.81 0.78 0.83 0.09 Total household expenditure per
person in the household 2,490 48.63 48.79 48.48 0.91
Assets owned (0-7) Minimum N
2,490 2431
0.54
0.58 1207
0.51 1224
0.35
Note: P-values are reported from Wald tests on the equality of means of Treatment and Control for each variable. Standard errors are clustered at the community level a One question was dropped from the Household Food Security Access Scale (HFIAS) at baseline
POVERTY AND PERCEIVED STRESS IN ZAMBIA
30
Table 2. Treatment effect on stress and indicators of poverty in Zambia’s Child Grant Programme (CGP) and Multiple Category Cash Transfer Programme (MCP), 36-months follow-up
Panel A: CGP
Perceived Stress Scale
(0-24)a
Expenditure per capitab
Household Food Insecurity Access
Scale (0-27)b
Number of non-productive assets
ownedb,c (1) (2) (3) (4)
Treatment effect
0.07
10.43***
-2.86***
0.72***
(t-statistic)
(0.21)
(4.32)
(-7.63)
(6.29)
Number of observations
2,273
2,273
2,269
2,272
Control mean (sd) 7.60 (4.20) 50.98 (36.97) 13.50 (5.20) 0.86 (1.44)
Treatment mean (sd) 7.70 (4.03) 62.52 (37.56) 10.54 (4.84) 1.71 (1.80)
Panel B: MCP
Treatment effect
-0.42
16.68***
-3.02***
0.37***
(t-statistic)
(-1.17)
(4.76)
(-6.94)
(5.73)
Number of observations
2,490
2,490
2,490
2,490
Control mean (sd) 9.92 (4.73) 60.54 (40.53) 14.50 (5.54) 0.49 (0.87)
Treatment mean (sd) 9.58(4.64) 76.87(53.62) 11.52(5.11) 0.84(0.97) Note: Impact estimated based on OLS regressions with and without controls. T-statistics are based on standard errors clustered at the community level. *** p<0.001, ** p<0.01, * p<0.05. a Control variables include age, education and marital status of the woman as well as poverty status at baseline (expenditure per capita, food insecurity and asset ownership), district, household size and demographic composition of the household. b Control variables include poverty status at baseline (expenditure per capita, food insecurity and asset ownership), district, household size and demographic composition of the household. c Number of assets owned range from 0-10 in the CGP and 0-7 in the MCP.
POVERTY AND PERCEIVED STRESS IN ZAMBIA
31
Table 3. Fixed-effect and cross-sectional OLS regressions of individual and household characteristics associated with the perceived stress scale, control groups only
CGP MCP
Cross-sectional OLS
regression (1)
Fixed-effect regression
(2)
Cross-sectional OLS regression
(3)
Age 0.02 - 0.01
(1.58) - (0.64) Education (attended school) 0.48 - -0.16
(1.74) - (-0.52) Any death in the household 0.53 1.63** -0.61
(0.58) (2.91) (-0.84) Household Food Insecurity Access Scale (0-27) 0.15** 0.12**
0.27***
(3.21) (2.77) (6.36) Expenditure per capita 0.01 0.00 -0.00
(1.78) (1.04) (-0.78) Number of non-productive assets owneda -0.01 -0.23
-0.08
(-0.05) (-1.37) (-0.42)
Constant 4.82*** 6.42*** 6.63***
(4.28) (9.18) (5.40)
Number of women 1,139 1,145 1,227 R-squared 0.09 0.04 0.18 Observations 1,145 2,285 Notes: Robust t-statistics in parentheses based on standard errors clustered at the community level. Cross-sectional models control for marital status, district, household size and demographic composition of the household. *** p<0.001, ** p<0.01, * p<0.05
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