A survey of the sustainability of Village Savings and Loans Associations (VSLAs) amid Covid-19 and its impact on household income levels: lessons from Malawi, Sub-Saharan Africa | BMC Public Health

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The objective

This study aimed to assess the factors associated with the sustainability of VSLAs in the midst of Covid-19 and its impacts on household income levels.

study design

This study used a quantitative method design to extrapolate in-depth information about the subject under study [30, 31]. In this study, we used an online cross-sectional survey. The study was conducted in Malawi, Africa. Malawi is located in the southern part of Africa, bordering countries like Zambia, Tanzania, and Mozambique. [32, 33]. It is one of the least developed countries in the world where the majority of its population still faces hunger, malnutrition and lives below the poverty line. [15, 34, 35]and depend mainly on agriculture for business and food for the population [36]. In Malawi, the study was specifically conducted in the town of Mzuzu, which is located in the northern part and the town has an estimated total population of 221,272 and an area of ​​143.8 square kilometers in 2019. The area of The study is politically divided into 14 rooms, namely; Chibanja, Chibavi West, Chibavi East, Chiputula, Jombo-Kaning’ina, Katawa, Lupaso-Nkhorongo, Luwinga, Masasa, Mchengautuwa East, Mchengautuwa West, Mzilawaingwe, Zolozolo East and Zolozolo West) as shown in Fig. 1. According to recent research, Mzuzu town is one of the fastest growing towns in Malawi mainly due to its socio-economic activity with most of its inhabitants dependent on agriculture, business and working as civil servants in many governmental and non-governmental organizations in the city [37]. Under these conditions, it was essential to conduct this study in this city to examine the impacts of Covid-19 which could have a negative influence on the socio-economic status of people.

Fig. 1

Mzuzu Study Area. Source: Authors 2021

Data collection procedures

We collected data from various VSLA members operating in Mzuzu town. The data collection exercise was carried out between November 2020 and January 2021. We recruited and trained a team of four research assistants, who were guided on the objectives and how to conduct the study. These research assistants helped identify VSLA groups and their members and facilitated the collection of the online survey led by Mr. Zolo (as head of research assistants). The questionnaire was sent to participants via Facebook, WhatsApp and email due to Covid-19 gathering restrictions, as the study was conducted while some social distancing measures were enforced in Malawi. Identified targeted respondents were provided with questionnaire links with the help of recruited research assistants.

Inclusion and exclusion criteria

All VSLA members operating in Mzuzu localities who were under the age of 18 were excluded from the survey. To ensure that respondents were from this country and city, a space was provided in the questionnaire where the respondent indicated their country and city of residence. All those who indicated outside the study areas were excluded.

Population, sample size and technique

The study recruited respondents who were members of VSLAs in the designated study area. A snowball and respondent-driven sampling technique was used to select the area and determine the sample population. We used this technique for the following reasons. First, it was easy to access the data because of the researchers’ links to people associated with VSLAs in the selected country. Second, due to the impact of Covid-19, it is not easy to collect the data physically, given the social distancing measures in place in all countries. [38,39,40].

We recruited 402 survey participants based on inclusion and exclusion criteria. We used a sampling calculation used by Yamane, with a confidence level of 95% and, P = 0.05 [41], NOT= Total population of Mzuzu City = 221,272 [37].

$$x=frac{N}{1+N{(e)}^{2}}$$

Which gave us 399, as the minimum number of participants required.

Questionnaire design

The questionnaire had three sections.

  1. I.

    Demographic data

    The first sections captured the socio-demographic data of VSLA members, which include; sex, age group, occupation, respondent’s level of education, status of household head and number of people in the house whose t were measured in the category and coded in binary form (Table 1 ).

  2. ii.

    Impact of Covid-19 on revenues

    The second part of the questionnaire collected data on the impact of Covid-19 on participants’ earnings. We asked respondents to indicate the category of income they earn per month before and during the Covid-19 epidemic. Income was broken down into categories/groups of three income brackets or levels. The first was those below 5,000 MK, then those below or above 5,000 MK but below 10,000 MK, and finally those above 10,000 MK (Table 1).

  3. iii.

    Performance and sustainability indicators

Table 1 Definitions and coding of variables

The third part of the questionnaire captured performance data that predicted the sustainability of VSLAs amid Covid-19 based on the literature. Members were asked about the impacts of Covid-19 on; repayment of the loan on time, frequency of obtaining the loan, contributions shared on time or not, and whether the members met. All variables were categorical and were measured in binary form (Table 1).

Validity and reliability

A pilot study was conducted to pre-test the instruments before the actual data collection which involved 43 respondents including members of VSLAs, masters and doctorates. students. The validity and reliability of the instrument was tested by sending the instrument to experts for comments before the actual data collection. The finding aid was tested using Cronbach’s alpha in SPSS and found to be 0.8.

Ethics clearance

The ethical clearance for this study was reviewed and approved by the School of Economics and Management of Yangtze University (approval number REF/YU/2020/08 (Fig. 3)) and the city council Mzuzu (MCC Approval Letter Reference Number/dated August 12, 2020 (Fig. 4)). Additionally, researchers have observed and followed the 1964 Declaration of Helsinki in research involving humans. Participation in the survey was voluntary and participants gave their informed consent to this questionnaire before completing it.

Data analysis

After collecting the data using the Google Form, we coded it in Microsoft Excel and then imported it into SPSS Version 23 for analysis. We presented the results of the descriptive statistics using frequency tables, graphs and diagrams. The chi-square test was performed to determine associations between sociodemographic variables and other variables. P-valuewas statistically significant at p

Specification of the econometric model

This was used to answer our second research question: predicting factors associated with VSLA sustainability. We used VSLA future certainty as the dependent variable, which was coded or characterized as a two-category variable. The coding was that if VSLA members attest that they have certainty about the future and sustainability of VSLAs regarding the current Covid-19 situation, then the value given was 1; otherwise, 0. Therefore, the dichotomy of directed and suggested dependent variables to us used the binary logistic regression model, which was found to fit the one used by other researchers[14, 42, 43].

In this study, a logistic regression model, the dichotomous variable is defined as follows:

$$y={int }_{0}^{1}while 1=Presence of Features 0=Absence of Features$$

while odd is defined as,

$$Odds=frac{p}{p-1}=frac{Probability of presence of characteristics}{Probability of absence of characteristics}$$

while the logit model definition is like this,

(Logitleft(pright)={beta }_{0}+{beta }_{1}{X}_{1}+{beta }_{2}{X}_{2 }+{beta }_{3}{X}_{3}+cdots +{beta }_{k}{X}_{k})[43, 44]

Where the probability of presence of the feature of interest is represented by p. The logit transformation is defined as the log of the odds.

(mathrm{log}left(frac{p}{1-p}right)=Logitleft(pright)={beta }_{0}+{beta }_{1} {X}_{1}+{beta }_{2}{X}_{2}+{beta }_{3}{X}_{3}+dots +{beta }_{k }{X}_{k}+e)[43, 44]

Whereas;

({beta}_{0})= constant,

({beta }_{1}-{beta }_{k})= are the logistic regression coefficients,

({X}_{1}-{X}_{k})= are independent explanatory variables, and.

(e)= is an error term.

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