Addressing the interaction between food insecurity, depression risk and informal work: findings of a cross-sectional survey among informal women workers with young children in South Africa

BMC women's health, Volume 21, No. 1, Year 2021

Interpretation

BACKGROUND: There is a high burden of depression globally, including in South Africa. Maternal depression is associated with poverty, unstable income, food insecurity, and lack of partner support, and may lead to poor outcomes for mothers and children. In South Africa one-third of working women are in informal work, which is associated with socioeconomic vulnerability. METHODS: A cross sectional survey explored work setting and conditions, food security and risk of depression among informal working women with young children (0-3 years). Depression risk was assessed using the Edinburgh Postnatal Depression Score (EPDS) and Whooley score. Food insecurity was evaluated using Household Food Insecurity Access Scale. Data was analysed using SPSS and Stata. RESULTS: Interviews were conducted with 265 informal women workers. Types of work included domestic work, home-based work, informal employees and own account workers, most of whom were informal traders. Most participants (149/265; 56.2%) earned between US$70-200 per month, but some participants (79/265; 29.8%) earned < US$70 per month, and few earned > US$200 per month (37/265; 14.0%). Many participants experienced mild (38/267; 14.3%), moderate (72/265; 27.2%) or severe (43/265; 16%) food insecurity. Severe food insecurity was significantly higher among participants with the lowest income compared to those with the highest income (p = 0.027). Women who received financial support from the baby’s father were less likely to be food insecure (p = 0.03). Using EPDS scores, 22/265 (8.3%) women were designated as being at risk of depression. This was similar among postnatal women and women with older children. Household food insecurity was significantly associated with depression risk (p < 0.001). CONCLUSIONS: Informal women workers were shown to be vulnerable with low incomes and high rates of food insecurity, thus increasing the risk for poor maternal health. However, levels of depression risk were low compared to previous estimates in South Africa, suggesting that informal workers may have high levels of resilience. Interventions to improve social protection, access to health services, and support for safe childcare in the workplace could improve the health and wellbeing of these mothers and support them to care for their children. A cross sectional survey methodology was employed to explore the work setting and conditions, income, food security and risk of depression among informal working women with children under the age of 3 years. The study was conducted in three primary health care (PHC) clinics in three townships in Durban, South Africa. In these areas unemployment is high at around 20%, with high rates of poverty, and an average annual income of R29 400 (USD2000) [33]. In addition, there is poor access to basic services including water and sanitation and informal housing is common, but most households do have access to electricity [34]. A recent study in Durban found that women in the informal economy work long hours and many only earn < R1000 (USD70) per month [27]. Primary caregivers of children living in a low-income household are entitled to an SA government provided Child Support Grant (CSG) of R420 (USD30) per month for each child [35]. Health care for pregnant women and children is provided free of charge in PHC clinics, and there are high rates of antenatal clinic attendance (94%) and facility-based delivery (96%) [36]. HIV prevalence is high among young women in KZN, with 41.1% of pregnant women attending government antenatal clinics testing HIV positive in 2017 [37]. Women were recruited while waiting in the queue in the three participating clinics. Trained fieldworkers approached women in the clinic waiting area and explained the study. Eligibility was determined using a structured screening tool based on the definition of informal work set out above (Additional file 1). Eligible participants were informal workers, aged 18 years or older, with a child under the age of 3 years. Informal workers were either informally employed or own account (self-employed) workers. Informally employed women were defined by: (1) receiving money from an employer; (2) having no formal work contract; and (3) not contributing to SA’s mandatory Unemployment Insurance Fund (UIF). Own-account workers provided goods and services directly to customers but were not tax registered or paying tax. Women were excluded from the study if they worked fewer than 3 days per week or had been in informal work for < 6 months in order to focus on those women with longer term experience of informal work. A stratified sampling approach was employed to recruit equal numbers of eligible women with children aged < 1 year (defined as the postnatal period) and mothers of children aged 12–35 months. Given the well-documented high risk of postnatal depression in SA, this approach was used to determine depression prevalence in the postnatal population compared to the wider population of informally working mothers. A sample size of 192 women (96 with children aged < 1 year and 96 with children aged 12–35 months) was required to detect a 20% difference in depression risk among postnatal women compared to the general population of informal working mothers. This sample size calculation assumes a 35% rate of depression risk in women with children 1– < 3 years of age with 95% probability and 80% power. Data collection was undertaken among women waiting in the queue in the three participating clinics. Trained fieldworkers approached women in the clinic waiting area and explained the study. Eligibility was determined using a structured screening tool based on the definition of informal work set out above. Data were collected using a structured questionnaire administered in the local language (IsiZulu) (Additional file 1), and data collection continued until the sample size was reached. All eligible women agreed to participate and the survey was conducted in a separate room in the clinic to ensure privacy. We recorded the type of work based on the mother’s reported occupation, workplace (home/street/employer’s premises) and working conditions (own account/self-employed/unpaid or paid in kind). Risk of depression was assessed using two tools validated for use in SA and translated into IsiZulu: the Edinburgh Postnatal Depression Scale (EPDS) [38, 39] and the Whooley score [6]. The EPDS is the most widely used screening tool for depression among postnatal women, and has been widely used and validated in many settings including in South Africa [40], including among populations of non-postnatal women [41] and in high HIV prevalence settings [42]. The EPDS employs a 7 day recall of depressive symptoms including anxiety, tearfulness and poor sleep. A cut-off score of ≥ 13 was used. Although a range of cut-off scores have been used in different settings, this cut-off has been most commonly used in South Africa [3, 6, 9, 10, 39, 43]. The Whooley questions are three questions to assess low mood and lack of interest as well as suicidal ideation. These two tools were used together to allow triangulation of the findings from two screening tools for depression risk. The USAID Household Food Insecurity Access Scale (HFIAS), adapted and translated to IsiZulu, was used to assess food insecurity. The HFIAS tool is a nine-item experience-based measure with questions about experiences of food insecurity of the past 4 weeks. The tool is designed to be easy to use and applicable to diverse sociocultural settings, and examines food security related to three domains: anxiety about food access; insufficient quality of food; and insufficient quantity of food [44]. The HFIAS can been shown to be broadly applicable across different cultural contexts and has been widely used and validated in Africa, including in South Africa [9, 22, 45] A professional psychologist, who was IsiZulu-speaking and had experience with both the EPDS and Whooley tools, trained the fieldworkers to assess depression risk using the two tools. The psychologist also supervised data collection to ensure the correct administration of the tools in the field. Quantitative analysis was undertaken using SPSS version 24 and Stata V15.1. Background characteristics, feeding and childcare practices, and conditions of informal work are presented as frequencies and proportions. To describe the types of work undertaken, participants were retrospectively categorised using a series of steps. Firstly, all women who reported they worked from home were categorised as home-based workers. Women were categorised as domestic workers if they reported they worked in a private household undertaking domestic or childcare work. All other women were categorised either as employees if they reported receiving a wage from an employer, or as own account workers if they were self-employed. Sub-categories of own account workers included informal traders and a variety of other own account jobs. For the EPDS high risk of depression was determined by a score of ≥ 13. Two positive answers were considered a positive score for the Whooley questions. For both tools a positive answer to questions about suicidal ideation was considered high depression risk, regardless of the answers to the other questions. Household food security was scored on a scale of 0–27, where 27 is the most food insecure, using the established and validated scoring for this tool [46]. For the multivariable analysis the food insecurity index was dichotomised into food secure (none or mild food insecurity) and food insecure (moderate or severe food insecurity), and the EPDS depression score was analysed on a continuous scale and means and standard deviations reported. The analysis was a two-step process. Initially a multi variable logistic model was used to identify factors associated with food insecurity. Due to the over dispersion of the EPDS depression score, a multi-variable negative binomial model including food insecurity was used to identify factors associated with PND score. In both cases only factors significant at p < 0.3 in bivariate analysis were included in the multi-variable model. Adjusted and unadjusted odds ratios and 95% confidence limits are reported. Stata V15.1 statistical software was used in the analysis All participating women provided written informed consent. Screening, consent processes and data collection were conducted in a private area in the PHC clinics. Referral procedures were established with staff at each of the PHC clinics to offer additional clinical and social support to participants as required. All women identified as at risk of depression or with any thoughts of self-harm were immediately referred to clinic staff for further assessment. Follow up support from a study counsellor was offered to all women identified as being at risk of depression. Women identified as having moderate or severe food insecurity were referred to a clinic-based social worker.

AI Digest

Study Justification:

– The study aimed to address the interaction between food insecurity, depression risk, and informal work among women with young children in South Africa.
– Maternal depression is associated with poverty, unstable income, food insecurity, and lack of partner support, which can have negative outcomes for both mothers and children.
– One-third of working women in South Africa are in informal work, which is associated with socioeconomic vulnerability.
– Understanding the relationship between these factors can inform interventions to improve the health and well-being of these mothers and support them in caring for their children.

Study Highlights:

– The study conducted a cross-sectional survey among 265 informal women workers with young children.
– Most participants earned between US$70-200 per month, with some earning less than US$70 per month.
– Many participants experienced mild, moderate, or severe food insecurity, with severe food insecurity being higher among those with the lowest income.
– Women who received financial support from the baby’s father were less likely to be food insecure.
– 8.3% of women were designated as being at risk of depression, which is lower than previous estimates in South Africa.
– Household food insecurity was significantly associated with depression risk.

Recommendations for Lay Reader and Policy Maker:

– Implement interventions to improve social protection for informal women workers, including access to health services and support for safe childcare in the workplace.
– Address the issue of low incomes and high rates of food insecurity among informal women workers to reduce the risk of poor maternal health.
– Provide financial support and resources to informal women workers, particularly those with young children, to improve their well-being and ability to care for their children.
– Promote partnerships and collaboration between government agencies, NGOs, and community organizations to address the complex challenges faced by informal women workers.

Key Role Players:

– Government agencies responsible for labor and social protection policies.
– NGOs working on women’s rights, poverty alleviation, and mental health.
– Community organizations providing support services to informal workers.
– Health care providers and clinics offering services to women and children.
– Social workers and counselors providing mental health support.

Cost Items for Planning Recommendations:

– Funding for social protection programs, including financial support for informal women workers.
– Resources for improving access to health services, including antenatal care and mental health support.
– Budget for training and capacity building of health care providers and social workers.
– Investment in safe childcare facilities and support in the workplace.
– Funding for research and monitoring to evaluate the effectiveness of interventions.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional survey conducted among informal women workers with young children in South Africa. The study provides information on work setting, conditions, income, food security, and risk of depression. The methodology and data analysis techniques are described. However, the abstract does not mention the sample size or the response rate, which are important factors in assessing the strength of the evidence. To improve the evidence, it would be helpful to include these details in the abstract.

Abstract

A cross sectional survey methodology was employed to explore the work setting and conditions, income, food security and risk of depression among informal working women with children under the age of 3 years. The study was conducted in three primary health care (PHC) clinics in three townships in Durban, South Africa. In these areas unemployment is high at around 20%, with high rates of poverty, and an average annual income of R29 400 (USD2000) [33]. In addition, there is poor access to basic services including water and sanitation and informal housing is common, but most households do have access to electricity [34]. A recent study in Durban found that women in the informal economy work long hours and many only earn < R1000 (USD70) per month [27]. Primary caregivers of children living in a low-income household are entitled to an SA government provided Child Support Grant (CSG) of R420 (USD30) per month for each child [35]. Health care for pregnant women and children is provided free of charge in PHC clinics, and there are high rates of antenatal clinic attendance (94%) and facility-based delivery (96%) [36]. HIV prevalence is high among young women in KZN, with 41.1% of pregnant women attending government antenatal clinics testing HIV positive in 2017 [37]. Women were recruited while waiting in the queue in the three participating clinics. Trained fieldworkers approached women in the clinic waiting area and explained the study. Eligibility was determined using a structured screening tool based on the definition of informal work set out above (Additional file 1). Eligible participants were informal workers, aged 18 years or older, with a child under the age of 3 years. Informal workers were either informally employed or own account (self-employed) workers. Informally employed women were defined by: (1) receiving money from an employer; (2) having no formal work contract; and (3) not contributing to SA’s mandatory Unemployment Insurance Fund (UIF). Own-account workers provided goods and services directly to customers but were not tax registered or paying tax. Women were excluded from the study if they worked fewer than 3 days per week or had been in informal work for < 6 months in order to focus on those women with longer term experience of informal work. A stratified sampling approach was employed to recruit equal numbers of eligible women with children aged < 1 year (defined as the postnatal period) and mothers of children aged 12–35 months. Given the well-documented high risk of postnatal depression in SA, this approach was used to determine depression prevalence in the postnatal population compared to the wider population of informally working mothers. A sample size of 192 women (96 with children aged < 1 year and 96 with children aged 12–35 months) was required to detect a 20% difference in depression risk among postnatal women compared to the general population of informal working mothers. This sample size calculation assumes a 35% rate of depression risk in women with children 1– < 3 years of age with 95% probability and 80% power. Data collection was undertaken among women waiting in the queue in the three participating clinics. Trained fieldworkers approached women in the clinic waiting area and explained the study. Eligibility was determined using a structured screening tool based on the definition of informal work set out above. Data were collected using a structured questionnaire administered in the local language (IsiZulu) (Additional file 1), and data collection continued until the sample size was reached. All eligible women agreed to participate and the survey was conducted in a separate room in the clinic to ensure privacy. We recorded the type of work based on the mother’s reported occupation, workplace (home/street/employer’s premises) and working conditions (own account/self-employed/unpaid or paid in kind). Risk of depression was assessed using two tools validated for use in SA and translated into IsiZulu: the Edinburgh Postnatal Depression Scale (EPDS) [38, 39] and the Whooley score [6]. The EPDS is the most widely used screening tool for depression among postnatal women, and has been widely used and validated in many settings including in South Africa [40], including among populations of non-postnatal women [41] and in high HIV prevalence settings [42]. The EPDS employs a 7 day recall of depressive symptoms including anxiety, tearfulness and poor sleep. A cut-off score of ≥ 13 was used. Although a range of cut-off scores have been used in different settings, this cut-off has been most commonly used in South Africa [3, 6, 9, 10, 39, 43]. The Whooley questions are three questions to assess low mood and lack of interest as well as suicidal ideation. These two tools were used together to allow triangulation of the findings from two screening tools for depression risk. The USAID Household Food Insecurity Access Scale (HFIAS), adapted and translated to IsiZulu, was used to assess food insecurity. The HFIAS tool is a nine-item experience-based measure with questions about experiences of food insecurity of the past 4 weeks. The tool is designed to be easy to use and applicable to diverse sociocultural settings, and examines food security related to three domains: anxiety about food access; insufficient quality of food; and insufficient quantity of food [44]. The HFIAS can been shown to be broadly applicable across different cultural contexts and has been widely used and validated in Africa, including in South Africa [9, 22, 45] A professional psychologist, who was IsiZulu-speaking and had experience with both the EPDS and Whooley tools, trained the fieldworkers to assess depression risk using the two tools. The psychologist also supervised data collection to ensure the correct administration of the tools in the field. Quantitative analysis was undertaken using SPSS version 24 and Stata V15.1. Background characteristics, feeding and childcare practices, and conditions of informal work are presented as frequencies and proportions. To describe the types of work undertaken, participants were retrospectively categorised using a series of steps. Firstly, all women who reported they worked from home were categorised as home-based workers. Women were categorised as domestic workers if they reported they worked in a private household undertaking domestic or childcare work. All other women were categorised either as employees if they reported receiving a wage from an employer, or as own account workers if they were self-employed. Sub-categories of own account workers included informal traders and a variety of other own account jobs. For the EPDS high risk of depression was determined by a score of ≥ 13. Two positive answers were considered a positive score for the Whooley questions. For both tools a positive answer to questions about suicidal ideation was considered high depression risk, regardless of the answers to the other questions. Household food security was scored on a scale of 0–27, where 27 is the most food insecure, using the established and validated scoring for this tool [46]. For the multivariable analysis the food insecurity index was dichotomised into food secure (none or mild food insecurity) and food insecure (moderate or severe food insecurity), and the EPDS depression score was analysed on a continuous scale and means and standard deviations reported. The analysis was a two-step process. Initially a multi variable logistic model was used to identify factors associated with food insecurity. Due to the over dispersion of the EPDS depression score, a multi-variable negative binomial model including food insecurity was used to identify factors associated with PND score. In both cases only factors significant at p < 0.3 in bivariate analysis were included in the multi-variable model. Adjusted and unadjusted odds ratios and 95% confidence limits are reported. Stata V15.1 statistical software was used in the analysis All participating women provided written informed consent. Screening, consent processes and data collection were conducted in a private area in the PHC clinics. Referral procedures were established with staff at each of the PHC clinics to offer additional clinical and social support to participants as required. All women identified as at risk of depression or with any thoughts of self-harm were immediately referred to clinic staff for further assessment. Follow up support from a study counsellor was offered to all women identified as being at risk of depression. Women identified as having moderate or severe food insecurity were referred to a clinic-based social worker.

Materials

https://efashare.b-cdn.net/materials/55d5dba265c7777da92948803675b8edeaec5498760893e96a5028bc589468bd/12905_2020_1147_MOESM1_ESM.pdf

Innovations

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health Clinics: Implementing mobile health clinics that can reach women in informal work settings, such as street vendors or domestic workers, can provide convenient access to maternal health services. These clinics can offer prenatal care, postnatal care, and mental health support, addressing the specific needs of informal working women.

2. Workplace Support Programs: Collaborating with employers in the informal sector to establish workplace support programs can help improve access to maternal health services. These programs can provide information, resources, and referrals to pregnant women and new mothers, ensuring they receive the necessary care and support while balancing their work responsibilities.

3. Financial Incentives: Introducing financial incentives, such as cash transfers or subsidies, for informal working women to seek maternal health services can help overcome financial barriers. These incentives can cover costs related to prenatal care, delivery, and postnatal care, making it more affordable for women to access the care they need.

4. Community Health Workers: Training and deploying community health workers within informal settlements or townships can bridge the gap between healthcare facilities and informal working women. These community health workers can provide education, counseling, and support, as well as facilitate referrals to appropriate healthcare services.

5. Telemedicine and Teleconsultations: Utilizing telemedicine and teleconsultation platforms can enable informal working women to access maternal health services remotely. Through video calls or phone consultations, women can receive medical advice, counseling, and follow-up care without the need for physical visits to healthcare facilities.

6. Partnerships with Non-Governmental Organizations (NGOs): Collaborating with NGOs that specialize in maternal health can help expand access to services for informal working women. These partnerships can provide funding, resources, and expertise to support initiatives aimed at improving maternal health outcomes in this vulnerable population.

It is important to note that the implementation of these innovations should be context-specific and tailored to the unique needs and challenges faced by informal working women in South Africa.

AI Innovations Description

Based on the description provided, the recommendation to improve access to maternal health for informal women workers with young children in South Africa is to implement interventions that focus on social protection, access to health services, and support for safe childcare in the workplace. These interventions can help improve the health and well-being of these mothers and support them in caring for their children. Additionally, addressing factors such as poverty, unstable income, and food insecurity, which are associated with maternal depression, can also contribute to better maternal health outcomes.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Increase social protection: Implement policies and programs that provide financial support to informal women workers, such as cash transfers or income supplementation. This can help alleviate poverty and improve access to healthcare services.

2. Improve access to health services: Enhance the availability and affordability of maternal health services in primary healthcare clinics. This can include ensuring adequate staffing, necessary medical equipment, and essential medications. Additionally, efforts should be made to reduce barriers to accessing healthcare, such as long waiting times or transportation challenges.

3. Support safe childcare in the workplace: Establish initiatives that promote safe and affordable childcare options for informal women workers. This can include setting up daycare centers or providing subsidies for childcare services. By addressing childcare needs, women can have peace of mind while working and have better access to maternal health services.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define indicators: Identify key indicators that reflect access to maternal health, such as the percentage of women receiving prenatal care, the percentage of facility-based deliveries, or the maternal mortality rate. These indicators should be measurable and relevant to the specific context.

2. Collect baseline data: Gather data on the selected indicators before implementing the recommendations. This can be done through surveys, interviews, or existing data sources. The baseline data will serve as a reference point for comparison.

3. Implement interventions: Implement the recommended interventions, such as social protection programs, improvements in healthcare services, and support for safe childcare. Ensure that these interventions are implemented consistently and effectively.

4. Monitor and evaluate: Continuously monitor the progress and impact of the interventions. Collect data on the selected indicators at regular intervals to assess any changes or improvements. This can be done through surveys, interviews, or data collection from healthcare facilities.

5. Analyze and compare data: Analyze the collected data and compare it to the baseline data. Look for any trends, patterns, or significant changes in the selected indicators. This analysis will help determine the impact of the interventions on improving access to maternal health.

6. Adjust and refine interventions: Based on the findings from the data analysis, make any necessary adjustments or refinements to the interventions. This can involve scaling up successful interventions, addressing any challenges or barriers, or identifying new areas for improvement.

7. Repeat the process: Continuously repeat the monitoring, evaluation, and adjustment process to ensure ongoing improvement in access to maternal health. This iterative approach allows for continuous learning and adaptation to achieve the desired outcomes.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions for further interventions or policy changes.

Authors & Co-Authors

Statistics:

Citations: 2

Authors: 6

Identifiers:

DOI: 10.1186/s12905-020-01147-7

Research Areas:

Community Interventions, Disparities, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Social Determinants

Study Countries:

South Africa

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Mixed-methods, Quantitative

Participants Gender:

Female