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. Author manuscript; available in PMC: 2019 Feb 22.
Published in final edited form as: Int J Soc Psychiatry. 2018 Nov 27;65(1):20–27. doi: 10.1177/0020764018814274

Food insecurity, mental distress and suicidal ideation in rural Africa: Evidence from Nigeria, Uganda and Ghana

Annika Claire Sweetland 1, Andrea Norcini Pala 2, Jennifer Mootz 1, Jennifer Chien-Wen Kao 3, Catherine Carlson 4, Maria A Oquendo 5, Bryan Cheng 3, Gary Belkin 6, Milton Wainberg 1
PMCID: PMC6386592  NIHMSID: NIHMS1008547  PMID: 30479180

Abstract

Background:

In sub-Saharan Africa, mental and substance-related disorders account for 19% of all years lived with disability, yet the intersection between poverty and mental distress is poorly understood since most psychiatric research is conducted in high-income countries.

Aims:

To examine the prevalence of and associations between food insecurity, mental distress and suicidal ideation in three rural village clusters in sub-Saharan Africa.

Method:

Cross-sectional multivariate analysis of sociodemographic variables associated with mental distress and suicidal ideation in three countries. The sample included 1,142 individuals from three rural village clusters in Nigeria (n = 380), Uganda (n = 380) and Ghana (n = 382). Food insecurity was measured based on the number of months in the previous year that the respondent’s family reported being ‘unable to eat two square meals per day’. Mental distress was assessed using the Kessler non-specific psychological distress scale (K6) and suicidal ideation was measured using an item from PRIME-MD. Other sociodemographic variables included gender, age, literacy and occupation.

Results:

The prevalence of individuals with moderate or severe mental distress in Nigeria, Uganda and Ghana were higher than previously reported in the literature: 35.5%, 30.8% and 30.4%, respectively, and suicidal ideation rates were 29.7%, 21.3% and 10.9%. No differences were observed in mental distress between men and women in any of the sites. Being a farmer (vs student or other) was protective for mental distress in two sites (Uganda and Ghana) but no other social indicators, such as age, gender, literacy and food insecurity, were significantly associated with mental distress. Risk for suicidal ideation differed across sites: it was associated with food insecurity in Nigeria, female gender in Uganda, and older age in Uganda.

Conclusions:

Mental distress and suicidal ideation were highly prevalent in three settings of extreme poverty across all groups, in ways that were not always consistent with the global literature. These findings suggest that more research is needed in to better understand the social etiology of mental distress in sub-Saharan Africa.

Keywords: Common mental disorders, LMICs, mental health, poverty, social determinants, sub-Saharan Africa

Introduction

Nearly, a third of all years lived with disability (YLD) can be attributed to mental disorders (Vigo, Thornicroft, & Atun, 2016). In sub-Saharan Africa, mental and substance use disorders account for 19% of all YLDs (Whiteford et al., 2013). Despite this, fewer than 15% of people in low-income countries with common mental disorders receive treatment (Anthes, 2016). Whereas there is an estimated 52.3 mental health providers per 100,000 in high-income countries, in Africa, this ratio is only 1.4 per 100,000 population (World Health Organization [WHO], 2015a). When treatment is provided in low-income settings, it is often below minimum standards due to a combination of stigma, low mental health literacy and limited services available. Furthermore, individuals with mental illness are frequently subjected to significant human rights abuses (WHO, 2016b). The two most common types of mental illness globally are depressive and anxiety disorders (Vigo et al., 2016). Because of the high comorbidity between depressive and anxiety symptoms (Lamers et al., 2011), in the present study, we examined them concurrently, employing the broader construct of mental distress, an often-utilized proxy for common mental disorders. Such an approach is additionally consonant with concerns that conceptual equivalence of discrete mental illnesses may not translate between cultures (Kleinman, 1987; Patel, 1998; Sweetland, Belkin, & Verdeli, 2014).

Little is known about mental distress in Sub-Saharan Africa since the majority of existing evidence comes from high-income countries. A recent review and meta-analysis of the global prevalence of common mental disorders found only eight studies from five African countries that met the inclusion criteria of (1) having been conducted among national or regional general population samples, (2) using clinical diagnostic interviews and (3) published between 1980 and 2013 (Steel et al., 2014). According to this meta-analysis, which included 174 prevalence studies from 63 countries, approximately 17.6% of individuals among the eight studies conducted in five sub-Saharan African countries met criteria for a mood, anxiety and/or substance use disorder during the previous 12 months and the pooled prevalence was 12.4% (Steel et al., 2014). This review indicates that prevalence can vary widely between settings, which could either reflect true variation or issues of measurement, such as cultural differences in reporting (Sweetland, Belkin, & Verdeli, 2014). In the World Mental Health Survey Initiative, 12-month prevalence of mood disorders in 18 countries ranged from 1.1% to 9.7%; for anxiety disorders, the range was from 3.0% to 19.0% (Kessler et al., 2009).

Even less is known about suicidal ideation, attempts, or completion rates in Sub-Saharan Africa. Suicide is the second leading cause of death among 15- to 29-year-olds worldwide, three-quarters of which are estimated to occur in low- and middle-income countries (LMIC) (WHO, 2015b). Global suicide rates also vary widely: from 0.4 to 44.2 per 100,000, with a global average of 11.4 per 100,000 (WHO, 2014). Men are twice as likely to die by suicide than women (WHO, 2014), while women may be more likely to have suicidal ideation, plans and attempts (Nock et al., 2008). Data from high-income countries (HICs) suggest greater risk for rural populations, possible risk factors include less access to mental health care (WHO, 2015a), socioeconomic decline and stigmatization of mental illness (Hirsch, 2006). Though a recent review of suicidal behavior in Africa estimated a low incidence of 3.2 per 100,000 population, this is likely a significant underestimation (Mars, Burrows, Hjelmeland, & Gunnell, 2014). According to the review, fewer than a third of African countries had reported regional or national suicide incidence data. Furthermore, a majority of the reported data was derived from hospital records, which may not be a reliable data source, especially in settings where much of the population has little or no access to the health care system. Social and cultural factors may have also contributed to underreporting, particularly in settings where suicidal behavior is illegal. According to 2012 WHO (2014) data, age-standardized suicide rates per 100,000 in the 3 countries included in this study – Ghana, Nigeria and Uganda – were 3.1, 6.5 and 19.5, respectively. Given that suicidal behavior is often preceded by suicidal ideation, more data about ideation in sub-Saharan Africa are needed.

The lack of evidence on mental health from Africa, home to many of the worlds’ lowest income countries, occurs despite growing interest in the mutually reinforcing relationship between poverty and mental disorders (WHO, 2007). Poverty increases risk for psychiatric disorders and distress, and the associated disability (e.g., not being able to work) may further exacerbate poverty in a vicious cycle (WHO, 2007). On the other hand, positive mental health is associated with better productivity and earnings, employment, educational achievement, health and quality of life (WHO, 2010). A review including 115 studies conducted in LMIC found that approximately three-quarters of the studies showed positive associations between poverty and depressive, anxious and somatoform symptoms, though some indicators of poverty exhibited a stronger relationship with these symptoms, inviting conclusions that a more precise examination of poverty indicators is warranted (Lund et al., 2010).

Food insecurity, defined as inadequate access to safe and nutritious food (WHO, 2017), has emerged as a poverty indicator of interest. Often cited for its adverse effect on health, a recent review of measures used to assess various dimensions of poverty found this indicator to have a strong and consistent association with common mental disorders (Lund et al., 2010). Indeed, positive associations between food insecurity and suicidal ideation are documented in HIV/AIDS patients in Uganda, postnatal mothers’ mental distress levels in Nepal and South Africa, and mental distress in a rural population in Zambia (Clarke et al., 2014; Cole & Tembo, 2011; Dewing, Tomlinson, le Roux, Chopra, & Tsai, 2013; Kinyanda, Hoskins, Nakku, Nawaz, & Patel, 2012). Explanations for this consistent relationship are both biological and social. For instance, qualitative data from Ethiopia have elucidated how food is an integral part of social ceremonies (e.g. funerals and hosting others), leading to stigma and feelings of shame when unable to entertain or participate in these events (Hadley, Stevenson, Tadesse, & Belachew, 2012). Participants in Burkina Faso have described feeling alienated from others and decreased household cohesion due to difficulties accessing food (Nanama & Frongillo, 2012). At a biological level, undernutrition can also contribute to or exacerbate depressive symptoms (Rao, Asha, Ramesh, & Rao, 2008). In non-human primates, adolescents with mothers who have experienced food insecurity exhibited reduced behavioral responsiveness to novel, stressful situations. However, there were no differences between non-human primate mothers who had and had not experienced food insecurity, suggesting that the effects of experiencing food insecurity may lessen with age, but re-emerge inter-generationally (Kinnally et al., 2013). Despite emerging research, the relationship between experiencing food insecurity and mental distress remains understudied (Compton, 2014). Even fewer studies have documented the relationship between food insecurity with suicidal ideation in a non-clinical population, particularly in Sub-Saharan Africa, which bears a disproportionate amount of malnourished and inadequately fed people due to low economic development and poor infrastructure (The Economist Intelligence Unit, 2014).

The purpose of this study was to examine the prevalence of and associations between food insecurity with mental distress and suicidal ideation in three settings of extreme poverty in rural Africa. The study uses 2006 baseline data from three village clusters of the Millennium Villages Project (MVP), an integrated, community-led, rural development program administered by the Earth Institute at Columbia University and Millennium Promise (MVP, 2016). The sites include Ruhiira, in Southwestern Uganda, Pampaida in the Northern state of Kaduna in Nigeria and Bonsaaso in the Amansie-West district of the Ashanti region. MVP sites were purposively selected for the integrated rural-development program to represent distinct agro-agricultural zones and as settings of extreme poverty, defined as having a minimum of 20% of children malnourished. At the time of data collection, an estimated 60%–90% of residents in these village clusters earned less than $1/day (MVP, 2016). Access to potable water in the Nigerian, Ugandan and Ghanaian sites, respectively, was 0% (compared to 59% nationally), 9% (compared to 66% nationally) and 41% (compared to 86% nationally) (MVP, 2016; The World Bank, 2016).

Methods

Sampling

A random group of 300 households were selected from each village cluster, from which 190 men and 190 women were selected for individual interviews.

Measures

Mental distress was assessed using the Kessler-6 (K6) non-specific psychological distress scale (Kessler et al., 2002) which consists of six items that ask individuals about symptoms associated with depression and/or anxiety. In HICs, this brief scale has demonstrated a high predictive ability to identify probable cases of mental disorders, since evidence suggests that individuals with a range of mental conditions tend to load high on non-specific mental distress (Dohrenwend, Shrout, Ergi, & Mendelsohn, 1980). Questions include the following: ‘during the past 30 days, about how often did you feel … 1) nervous?, 2) hopeless?, 3) restless or fidgety?, 4) so depressed that nothing could cheer you up?, 5) that everything was an effort?, and 6) worthless?’ Response options included a 5-point Likert-type scale ranging from ‘none of the time’ to ‘all of the time’. The sum of these six items was used to calculate an overall distress score ranging from 0 to 24. The K6 scale for non-specific psychological distress has been used in sub-Saharan Africa demonstrating moderate psychometric properties (Andersen et al., 2011).

Suicidal ideation was measured using an item from PRIME-MD (Spitzer, Kroenke, & Williams, 1999): ‘do you have thoughts that it would be better if you were dead or of hurting yourself?’ Responses were recorded on a 5-point Likert-type scale ranging from ‘none of the time’ to ‘all of the time’ and were dichotomized in our analyses to represent the presence or absence of any suicidal thoughts. Food insecurity along with several sociodemo-graphic variables (gender, age, literacy and occupation) were included in the analyses. Food insecurity was measured based on the number of months in the previous year that the respondent’s family reported being ‘unable to eat two square meals per day’. Literacy was assessed by the affirmative response to two questions asked to the head of household: ‘can [name] read in any language’ and ‘can [name] write in any language?’ A negative response to either of these questions was considered ‘not literate’. Occupation was classified into three groups: farmer, student or ‘other’.

Statistical methods

In the absence of pre-established cut-off scores for these settings, we used the cut off scores suggested by Kessler et al. (2010) including four categories corresponding to no or mild symptoms (K6 = 0–7) and moderate or severe symptoms (K6 = 8 or higher). Two logistic regressions were performed using Mplus 7.4 (Muthen & Muthen, 2012) to test the association of mental health distress and suicidal ideation with social covariates. First, we imputed missing data using the Marcov Chain Monte Carlo method. We used Weighted Least Square Mean and Variance adjusted (WLSMV) as the default estimator for binary variables. The estimates are probit coefficients which express the change in the outcome for a unit increase in the predictor. Internal reliability of the instrument was tested using ordinal alpha, which, compared to Cronbach’s alpha, produces more accurate estimation when Likert-type rating scales are analyzed (Zumbo, Gadermann, & Zeisser, 2007).

Results

Socio-demographic characteristics

The final sample included 1,142 individuals from three rural village clusters in Nigeria (n = 380), Uganda (n = 380) and Ghana (n = 382). The sociodemographic characteristics of each sample are included in Table 1. Though relatively balanced with regard to gender, the Uganda sample was significantly younger than Nigeria and Ghana, with 70.8% under the age of 34 and only one individual over the age of 50. This finding is not surprising given that Uganda has the youngest population globally with almost 80% of its population being under age 30 and over 50% of its population being under age 15 (Population Secretariat, 2012). Literacy was higher in Ghana and Uganda (56.5% and 73.7%, respectively) than in Nigeria (17.4%). The majority of all samples was comprised of farmers though a slightly larger proportion of Nigerians fell into the ‘other’ category. The average number of months of food insecurity in the previous year in Nigeria, Uganda and Ghana were 0.48, 1.80 and 0.75, respectively.

Table 1.

Population sociodemographics of Nigerian, Ugandan and Ghanian rural villages.

Nigeria (n = 380) Uganda (n = 380) Ghana (n = 382)
Gender
 Male 141 37.1% 174 45.8% 182 47.6%
 Female 145 38.2% 185 48.7% 195 51.0%
 Missing 94 24.7% 21 5.5% 5 1.3%
Age
 13–34 200 (52.6%) 269 (70.8%) 220 (57.6%)
 35–49 93 (24.5%) 97 (25.5%) 102 (26.7%)
 50–64 58 (15.3%) 1 (0.3%) 23 (6.0%)
 >65 years 13 (3.4%) 0 (0.0%) 19 (5.0%)
 Missing 16 (4.2) 13 (3.4%) 18 (4.7%)
Literacy
 Literate 66 (17.4%) 278 (73.7%) 216 (56.5%)
 Not literate 214 (56.3%) 72 (19.2%) 160 (41.9%)
 Missing 100 (26.3%) 27 (7.1 %) 6 (1.6%)
Occupation
 Farmer 1 89 (49.7%) 274 (72.1 %) 293 (76.7%)
 Student 12 (3.2%) 0 (0.0%) 60 (15.7%)
 Other 83 (21.8%) 71 (18.7%) 23 (6.0%)
 Missing 96 (25.3%) 35 (9.2%) 6 (1.6%)
Food insecurity
 Average number of months 0.48 SD = 0.96 1.83 SD = 3.19 0.75 SD = 1.17
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Mental health outcomes

The prevalence of individuals with moderate or severe mental distress in Nigeria, Uganda and Ghana was 35.5%, 30.8% and 30.4%, respectively (see Table 2). The corresponding suicidal ideation rates were 29.7%, 21.3% and 9.7% (see Table 2). No differences were observed in mental distress between men and women in any of the sites; however, in Uganda, women had greater risk for suicidal thoughts (β = 0.774, p < .001) (see Table 3). In both Uganda and Ghana, being a farmer (versus student or other) was protective for mental distress (β =−0.518, p < .05 and β =−0.862, p < .05, respectively). No other social indicators, such as age, gender, literacy, occupation and food insecurity, were significantly associated with mental distress. K6 mental distress scores were significantly associated with suicidal ideation in all countries (Nigeria β = 0.731, p < .001; Uganda β = 0.584, p < .001; and Ghana β = 0.350, p < .001). The only risk factor for suicidal ideation in Nigeria was food insecurity (β =−0.255, p < .05), and in Ghana suicidal thoughts were associated with older age (β = 0.218, p < .05).

Table 2.

Prevalence of mental distress suicidal ideation across sites.

Nigeria (n = 380) Uganda (n = 380) Ghana (n = 382)
K6
 None or mild (score 0–7) 246 (64.7%) 263 (69.2%) 266 (69.6%)
 Moderate or severe (score 8–24) 134 (35.3%) 117 (30.8%) 116 (30.4%)
Suicidal ideation
 No 267 (70.3%) 299 (78.7%) 303 (79.3%)
 Yes 113 (29.7%) 81 (21.3%) 37 (9.7%)
 Missing 0 (0%) 0 (0%) 42(11.0%)
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Table 3.

Social factors associated with mental distress.

Nigeria Uganda Ghana
BETA p-value BETA p-value BETA p-value
K6
 Food insecurity 0.177 0.074 0.133 0.498 −0.120 0.085
 Female gender 0.184 0.387 −0.215 0.288 −0.198 0.139
 Literate −0.079 0.678 −0.410 0.220 0.152 0.301
 Occupation: Farmer −0.007 0.989 −0.518 0.017 −0.862 0.013
 Occupation: Student 0.042 0.848 n/a n/a 0.106 0.742
 Age group 0.100 0.389 0.406 0.203 −0.139 0.059
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p<.05.

Discussion

Given the dearth of evidence examining the social risk factors associated with mental distress and suicidal ideation in sub-Saharan Africa, this study fills an important gap in the literature. Mental distress and suicidal ideation were very high in all three sites, but sociodemographic risk factors were not consistent with those often reported in the literature. Mental distress was double the rate previously found in a population-based study in Zambia (14.1%) (Chipimo & Fylkesnes, 2009) or among working adults in Ethiopia (17.7%) (Gelaye et al., 2012), but lower than rates found in three subpopulations in Ethiopia: university students (40.9%) (Dachew, Azale Bisetegn, & Berhe Gebremariam, 2015), Leprosy outpatients (52.4%) (Leekassa, Bizuneh, & Alem, 2004) and caregivers of people with severe mental illness (56.7%) (Sintayehu, Mulat, Yohannis, Adera, & Fekade, 2015). Rates were similar to a sample of tuberculosis patients (32.9%) and higher than for hospital outpatients (17.1%) in South Africa (Peltzer, Naidoo, et al., 2012; Peltzer, Pengpid, & Skaal, 2012).

Suicidal ideation was significantly higher than that shown in previous studies conducted in Nigeria and Uganda, and to our knowledge, this is the first study to assess suicidal ideation in Ghana. Nearly one third of Nigerians (29.7%) endorsed suicidal thoughts, nearly four times higher than rates observed in a recent population survey in Lagos state (7.3%) (Adewuya et al., 2016) almost 10 times higher than the 3.2% lifetime prevalence found among a nationally representative population study through the World Mental Health Survey (Gureje et al., 2007). In Uganda, roughly one fifth (21.3%) reported suicidal ideation, which was consistent with the 20.5% of individuals in two districts of Northern Uganda (Ovuga, Boardman, & Wasserman, 2005) and higher than the 7.8% ‘moderate to high risk for suicidality’ observed among HIV outpatients in central Uganda (Kinyanda et al., 2012).

Interestingly, food insecurity was not associated with greater mental distress in any of the sites. This finding contrasts with several studies in the United States, Canada and France that found food insecurity to be associated with mental distress (Liu, Njai, Greenlund, Chapman, & Croft, 2014), suicidal ideation (Davison, Marshall-Fabien, & Tecson, 2015), and depression and suicidal ideation (Pryor et al., 2016), respectively. Two studies in Ethiopia also found greater mental distress among pregnant women in households experiencing food insecurity (Jebena et al., 2015) and higher symptoms of anxiety and depression among a random selection of adults with food insecurity (Hadley et al., 2008). Food insecurity was, however, a risk factor for suicidal ideation in Nigeria, consistent with findings from other settings (Davison et al., 2015; Dewing et al., 2013; Pryor et al., 2016). However, the relation between food insecurity and suicidal ideation was not observed in the other two sites. It could be that contextual circumstances and expectations regarding food insecurity play an important role on whether and how food insecurity impacts mental health. In Zambia, for instance, people experienced higher mental distress when faced with food shortages during the dry season, a time not typically characterized by problems accessing food (Cole & Tembo, 2011).

Several other expected differences were not observed in our sample. For example, although globally demographic distributions demonstrate that women tend to have greater risk for depression and anxiety, whereas men have greater risk for substance addiction and antisocial disorders (WHO, 2016a), no gender differences were observed in relation to mental distress in any site. Also, although elderly Nigerians in the World Mental Health Survey Initiative had greater risk for major depressive disorder, no differences by age were observed in our samples. These associations were observed with regard to suicidal ideation in one setting: women and older individuals had greater risk for suicidal ideation in Uganda. Being a farmer (versus student or other) was protective for mental distress in Uganda and Ghana.

There are several limitations to this study. First, as a cross-sectional assessment, it is not possible to establish causality. Second, because the targeted population was poor and rural, the sample was not representative of the general population. Third, since the socioeconomic survey (which was conducted at the household level) and health survey (done at the individual level) were not always conducted in the same households, there is some missing sociodemographic data. Given that the item used to assess suicidal ideation was a broad double-barreled question evaluating on the one hand passive thoughts of suicide (‘it would be better if you were dead’) or non-lethal self-harm (‘… or of hurting yourself), and not directly whether the person had the explicit intent to kill him or herself may have distorted the reporting of this symptom. Finally, while the data are somewhat outdated, they still have value given the scarcity of research in this area.

The MVP sites, selected as contexts of extreme poverty relative to the LMIC settings they were in, showed high levels of measured distress and suicidality. These issues were not addressed as part of the MVP package of interventions which focused more on closing agricultural, educational and economic productivity and key physical health (infectious disease and maternal-infant health) gaps. While this study confirmed the burden of mental distress in poor, rural areas in sub-Saharan Africa to be high, the lack of associations between sociodemographic variables and food insecurity with mental distress indicates that the mechanisms through which poverty and mental distress reinforce one another remain unclear, an important area for future research. For instance, though it is commonly believed that addressing poverty will necessarily improve mental health, in fact, more consistent evidence suggests that the opposite is true: treating mental disorders is associated with socioeconomic improvement (Lund et al., 2010).

Following the incorporation of mental health in the 2030 United Nations’ Sustainable Development Goals, in April 2016, the WHO, World Bank and the US National Institute of Mental Health hosted a joint high-level meeting to make mental health a global development priority (The World Bank & WHO, 2016). In this meeting, the World Bank recognized that, ‘each dollar invested in easily scalable mental health treatment and services for depression and anxiety returns about US$4 in improved health and ability to work’ (The World Bank & WHO, 2016). Integrated research platforms and data gathering efforts can establish how and in which ways incorporating mental health treatment in development programs may significantly improve both socioeconomic and health outcomes, providing a boost to further lift communities out of extreme poverty and enhance wellbeing.

Acknowledgements

The authors wish to thank the Earth Institute at Columbia University and Millennium Villages Project for providing the data and to Bryan Chen and Eleni Vousoura for data cleaning and management.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded, in part, through the US National Institute of Mental Health (K01 MH104514; T32-MH19139; T32 MH096724).

References

  1. Adewuya AO, Ola BA, Coker OA, Atilola O, Zachariah MP, Olugbile O, … Idris O (2016). Prevalence and associated factors for suicidal ideation in the Lagos State Mental Health Survey, Nigeria. BJPsych Open, 2, 385–389. doi: 10.1192/bjpo.bp.116.004333 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Andersen LS, Grimsrud A, Myer L, Williams DR, Stein DJ, & Seedat S (2011). The psychometric properties of the K10 and K6 scales in screening for mood and anxiety disorders in the South African stress and health study. International Journal of Methods in Psychiatric Research, 20, 215–223. doi: 10.1002/mpr.351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Anthes E (2016). Pocket psychiatry. Nature, 532, 20–24. [DOI] [PubMed] [Google Scholar]
  4. Chipimo PJ, & Fylkesnes K (2009). Mental distress in the general population in Zambia: Impact of HIV and social factors. BMC Public Health, 9(1), Article 298. doi: 10.1186/1471-2458-9-298 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Clarke K, Saville N, Shrestha B, Costello A, King M, Manandhar D, … Prost A (2014). Predictors of psychological distress among postnatal mothers in rural Nepal: A cross-sectional community-based study. Journal of Affective Disorders, 156, 76–86. doi: 10.1016/j.jad.2013.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cole SM, & Tembo G (2011). The effect of food insecurity on mental health: Panel evidence from rural Zambia. Social Science & Medicine, 73, 1071–1079. doi: 10.1016/j.socscimed.2011.07.012 [DOI] [PubMed] [Google Scholar]
  7. Compton MT (2014). Food insecurity as a social determinant of mental health. Psychiatric Annals, 44, 46–51. doi: 10.3928/00485713-20140108-08 [DOI] [Google Scholar]
  8. Dachew BA, Azale Bisetegn T, & Berhe Gebremariam R (2015). Prevalence of mental distress and associated factors among undergraduate students of University of Gondar, Northwest Ethiopia: A cross-sectional institutional based study. PLoS ONE, 10(3), e0119464. doi: 10.1371/journal.pone.0119464 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Davison KM, Marshall-Fabien GL, & Tecson A (2015). Association of moderate and severe food insecurity with suicidal ideation in adults: National survey data from three Canadian provinces. Social Psychiatry and Psychiatric Epidemiology, 50, 963–972. doi: 10.1007/s00127-015-1018-1 [DOI] [PubMed] [Google Scholar]
  10. Dewing S, Tomlinson M, le Roux IM, Chopra M, & Tsai AC (2013). Food insecurity and its association with cooccurring postnatal depression, hazardous drinking, and suicidality among women in peri-urban South Africa. Journal of Affective Disorders, 150, 460–465. doi: 10.1016/j.jad.2013.04.040 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Dohrenwend BP, Shrout PE, Ergi G, & Mendelsohn FS (1980). Measures of non-specific psychological distress and other dimensions of psychopathology in the general population. Archives of General Psychiatry, 37, 1229–1236. [DOI] [PubMed] [Google Scholar]
  12. The Economist Intelligence Unit. (2014). Food security in focus: Sub-Saharan Africa 2014. Available from http://foodsecurityindex.eiu.com/
  13. Gelaye B, Lemma S, Deyassa N, Bahretibeb Y, Tesfaye M, Berhane Y, & Williams MA (2012). Prevalence and correlates of mental distress among working adults in Ethiopia. Clinical Practice and Epidemiology in Mental Health, 8, 126–133. doi: 10.2174/1745017901208010126 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gureje O, Kola L, Uwakwe R, Udofia O, Wakil A, & Afolabi E (2007). The profile and risks of suicidal behaviours in the Nigerian Survey of Mental Health and Well-Being. Psychological Medicine, 37, 821–830. doi: 10.1017/s0033291707000311 [DOI] [PubMed] [Google Scholar]
  15. Hadley C, Stevenson EG, 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, 2412–2419. doi: 10.1016/j.socscimed.2012.09.018 [DOI] [PubMed] [Google Scholar]
  16. Hadley C, Tegegn A, Tessema F, Cowan JA, 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 & Community Health, 62, 980–986. doi: 10.1136/jech.2007.068460 [DOI] [PubMed] [Google Scholar]
  17. Hirsch JK (2006). A review of the literature on rural suicide: Risk and protective factors, incidence, and prevention. Crisis, 27, 189–199. doi: 10.1027/0227-5910.27.4.189 [DOI] [PubMed] [Google Scholar]
  18. Jebena MG, Taha M, Nakajima M, Lemieux A, Lemessa F, Hoffman R, … al’Absi M (2015). Household food insecurity and mental distress among pregnant women in Southwestern Ethiopia: A cross sectional study design. BMC Pregnancy Childbirth, 15, Article 250. doi: 10.1186/s12884-015-0699-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S, Ormel J, … Wang PS (2009). The global burden of mental disorders: An update from the WHO World Mental Health (WMH) Surveys. Epidemiologia e psichiatria sociale, 18(1), 23–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, … Zaslavsky AM (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32, 959–976. [DOI] [PubMed] [Google Scholar]
  21. Kessler RC, Green JG, Gruber MJ, Sampson NA, Bromet E, Cuitan M, … Zaslavsky AM (2010). Screening for serious mental illness in the general population with the K6 Screening scale: Results from the WHO World Mental Health (WMH) Survey initiative. International Journal of Methods in Psychiatric Research, 19 (Suppl. 1), 4–22. doi: 10.1002/mpr.310 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kinnally EL, Feinberg C, Kim D, Ferguson K, Coplan JD, & Mann JJ (2013). Transgenerational effects of variable foraging demand stress in female bonnet macaques. American Journal of Primatology, 75, 509–517. doi: 10.1002/ajp.22130 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kinyanda E, Hoskins S, Nakku J, Nawaz S, & Patel V (2012). The prevalence and characteristics of suicidality in HIV/AIDS as seen in an African population in Entebbe district, Uganda. BMC Psychiatry, 12, [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kleinman A (1987). Anthropology and psychiatry: The role of culture in cross-cultural research. British Journal of Psychiatry, 151, 447–454. [DOI] [PubMed] [Google Scholar]
  25. Lamers F, van Oppen P, Comijs HC, Smit JH, Spinhoven P, van Balkom AJ, … Penninx BW (2011). Comorbidity patterns of anxiety and depressive disorders in a large cohort study: The Netherlands Study of Depression and Anxiety (NESDA). The Journal of Clinical Psychiatry, 72, 341–348. doi: 10.4088/JCP.10m06176blu [DOI] [PubMed] [Google Scholar]
  26. Leekassa R, Bizuneh E, & Alem A (2004). Prevalence of mental distress in the outpatient clinic of a specialized leprosy hospital. Addis Ababa, Ethiopia, 2002. Leprosy Review, 75, 367–375. [PubMed] [Google Scholar]
  27. Liu Y, Njai RS, Greenlund KJ, Chapman DP, & Croft JB (2014). Relationships between housing and food insecurity, frequent mental distress, and insufficient sleep among adults in 12 US States, 2009. Preventing Chronic Disease, 11, Article E37. doi: 10.5888/pcd11.130334 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lund C, Breen A, Flisher AJ, Kakuma R, Corrigall J, Joska JA, … Patel V (2010). Poverty and common mental disorders in low and middle income countries: A systematic review. Social Science & Medicine, 71, 517–528. doi: 10.1016/j.socscimed.2010.04.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Mars B, Burrows S, Hjelmeland H, & Gunnell D (2014). Suicidal behaviour across the African continent: A review of the literature. BMC Public Health, 14, Article 606. doi: 10.1186/1471-2458-14-606 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Millennium Villages Project. (2016). Available from http://millenniumvillages.org/
  31. Muthen LK, & Muthen BO (2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Author. [Google Scholar]
  32. Nanama S, & Frongillo EA (2012). Altered social cohesion and adverse psychological experiences with chronic food insecurity in the non-market economy and complex households of Burkina Faso. Social Science & Medicine, 74, 444–451. doi: 10.1016/j.socscimed.2011.11.009 [DOI] [PubMed] [Google Scholar]
  33. Nock MK, Borges G, Bromet EJ, Alonso J, Angermeyer M, Beautrais A, … Williams D (2008). Cross-national prevalence and risk factors for suicidal ideation, plans and attempts. The British Journal of Psychiatry, 192, 98–105. doi: 10.1192/bjp.bp.107.040113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Ovuga E, Boardman J, & Wasserman D (2005). The prevalence of depression in two districts of Uganda. Social Psychiatry and Psychiatric Epidemiology, 40, 439–445. doi: 10.1007/s00127-005-0915-0 [DOI] [PubMed] [Google Scholar]
  35. Patel V (1998). Culture and common mental disorders in Sub-Saharan Africa. New York, NY: Psychology Press. [Google Scholar]
  36. Peltzer K, Naidoo P, Matseke G, Louw J, McHunu G, & Tutshana B (2012). Prevalence of psychological distress and associated factors in tuberculosis patients in public primary care clinics in South Africa. BMC Psychiatry, 12, Article 89. doi: 10.1186/1471-244x-12-89 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Peltzer K, Pengpid S, & Skaal L (2012). Prevalence of psychological distress and associated factors in urban hospital outpatients in South Africa. South African Journal of Psychiatry, 18(1), 10–15. [Google Scholar]
  38. Population Secretariat. (2012). State of Uganda population report 2012. Retrieved from https://Ugandalibrary.health.go.ug/download/file/fid/200.
  39. Pryor L, Lioret S, van der Waerden J, Fombonne E, Falissard B, & Melchior M (2016). Food insecurity and mental health problems among a community sample of young adults. Social Psychiatry and Psychiatric Epidemiology, 51, 1073–1081. doi: 10.1007/s00127-016-1249-9 [DOI] [PubMed] [Google Scholar]
  40. Rao TSS, Asha MR, Ramesh BN, & Rao KSJ (2008). Understanding nutrition, depression and mental illnesses. Indian Journal of Psychiatry, 50, 77–82. doi: 10.4103/0019-5545.42391 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Sintayehu M, Mulat H, Yohannis Z, Adera T, & Fekade M (2015). Prevalence of mental distress and associated factors among caregivers of patients with severe mental illness in the outpatient unit of Amanuel Hospital, Addis Ababa, Ethiopia, 2013: Cross-sectional study. Journal of Molecular Psychiatry, 3(1), Article 9. doi: 10.1186/s40303-015-0014-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Spitzer RL, Kroenke K, & Williams JB (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. Primary care evaluation of mental disorders. Patient health questionnaire. Journal of the American Medical Association, 282, 1737–1744. [DOI] [PubMed] [Google Scholar]
  43. Steel Z, Marnane C, Iranpour C, Chey T, Jackson JW, Patel V, & Silove D (2014). The global prevalence of common mental disorders: A systematic review and meta-analysis 1980–2013. International Journal of Epidemiology, 43, 476–493. doi: 10.1093/ije/dyu038 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Sweetland AC, Belkin GS, & Verdeli H (2014). Measuring depression and anxiety in sub-saharan Africa. Depression and Anxiety, 31, 223–232. doi: 10.1002/da.22142 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Vigo D, Thornicroft G, & Atun R (2016). Estimating the true global burden of mental illness. The Lancet Psychiatry, 3, 171–178. doi: 10.1016/S2215-0366(15)00505-2 [DOI] [PubMed] [Google Scholar]
  46. Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, … Vos T (2013). Global burden of disease attributable to mental and substance use disorders: Findings from the global burden of disease study 2010. The Lancet, 382, 1575–1586. doi: 10.1016/S0140-6736(13)61611-6 [DOI] [PubMed] [Google Scholar]
  47. The World Bank. (2016). World DataBank: World development indicators. Retrieved from http://databank.worldbank.org/data/reports.aspx?source=2&country=UGA&series=&period=
  48. The World Bank, & World Health Organization. (2016). Out of the shadows: Making mental health a global priority. Washington, DC: Retrieved from http://www.worldbank.org/en/events/2016/03/09/out-of-the-shadows-making-mental-health-a-global-priority [Google Scholar]
  49. World Health Organization. (2007). Breaking the vicious cycle between mental ill-health and poverty. Retrieved from http://www.who.int/mental_health/policy/development/1_Breakingviciouscycle_Infosheet.pdf
  50. World Health Organization. (2014). Preventing suicide: A global imperative. Geneva, Switzerland: Author. [Google Scholar]
  51. World Health Organization. (2015a). Mental health atlas 2014. Geneva, Switzerland: Author. [Google Scholar]
  52. World Health Organization. (2015b). Suicide: Fact sheet 398. Retrieved from http://www.who.int/mediacentre/factsheets/fs398/en/
  53. World Health Organization. (2016a). Gender disparities and mental health: The facts. Retrieved from http://www.who.int/mental_health/prevention/genderwomen/en/
  54. World Health Organization. (2016b). Mental health, human rights and legislation. Retrieved from https://www.who.int/mental_health/policy/legislation/en/
  55. World Health Organization. (2017). Nutrition. Retrieved from http://www.who.int/nutrition/en/
  56. World Health Organization, & United Nations. (2010). Mental health and development: Integrating mental health into all development efforts including MDGs. Retrieved from http://www.who.int/mental_health/policy/mhtargeting/mh_policyanalysis_who_undesa.pdf
  57. Zumbo BD, Gadermann AM, & Zeisser C (2007). Ordinal versions of coefficients alpha and theta for Likert Rating Scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29. [Google Scholar]

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