| Literature DB >> 35641969 |
George N Chidimbah Munthali1,2,3, Xuelian Wu4, Mastano Nambiro Woleson Dzimbiri5, Amon Zolo3, John K B Mushani3, Lazarus Obed Livingstone Banda6.
Abstract
BACKGROUND: Food security, malnutrition, and poverty are some of the challenges that most of the sub-Saharan African countries have been historically facing. With the coming of Covid-19 pandemic, the sustainability of the Village Savings and Loans Association which are formed to counter fight these challenges is questioned. AIM: This study aimed to assess factors associated with the Sustainability of VSLAs amidst Covid-19 and its impacts on households' income levels.Entities:
Keywords: Covid-19; Developing Economies; Households Income; Inequality of Income; VSLAs
Mesh:
Year: 2022 PMID: 35641969 PMCID: PMC9152667 DOI: 10.1186/s12889-022-13303-9
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 4.135
Fig. 1Study Area of Mzuzu. Source: Authors 2021
Variables definitions and coding
| Variables | Category | Categorical Variables Coding | |
|---|---|---|---|
| Gender | Male | 259 | 0 |
| Female | 142 | 1 | |
| Age-group | < 30 | 157 | 0 |
| ≥ 31 years old | 244 | 1 | |
| Occupation | Otherwise | 288 | 0 |
| Employed i.e. Civil servant or NGOs | 113 | 1 | |
| Education Level | otherwise | 14 | 0 |
| attended education | 387 | 1 | |
| Are you head of the house | No | 122 | 0 |
| Yes | 279 | 1 | |
| Number of people in the house | ˂5 members | 139 | 0 |
| 6 ≥ | 262 | 1 | |
| Loan Repayment not on time | No | 77 | 0 |
| Yes | 324 | 1 | |
| Loan obtainment Frequency | Decreased | 274 | 1 |
| Increased | 127 | 0 | |
| Shares contribution not time | No | 89 | 0 |
| Yes | 312 | 1 | |
| Meeting’s continuations | No | 160 | 0 |
| Yes | 241 | 1 | |
Source: Authors 2021 Coded Using SPSS Software
Fig. 3Ethical clearance of the study
Fig. 4Approval letter from Mzuzu City Council (MCC) in Malawi
Social demographic characteristics and Future of VSLAs (N = 402)
| Variables | Category | Future of VSLAs Is | n | % | χ2 Test | ||
|---|---|---|---|---|---|---|---|
| Gender | Male | 131 | 128 | 259 | 64.4279 | 4.462 | |
| Female | 88 | 55 | 142 | 35.3234 | |||
| Age group | < 30 | 56 | 101 | 157 | 39.0547 | 36.749 | |
| ≥ 31 years old | 163 | 82 | 244 | 60.6965 | |||
| Occupation | Otherwise | 152 | 137 | 288 | 71.6418 | 1.469 | 0.225 |
| Employed | 67 | 46 | 113 | 28.1095 | |||
| Education Level | otherwise | 1 | 13 | 14 | 3.48259 | 13.105 | |
| attended education | 218 | 170 | 387 | 96.2687 | |||
| Head of the house | No | 118 | 65 | 122 | 30.3483 | 4.249 | . |
| Yes | 162 | 57 | 279 | 69.403 | |||
| Household Total (Pple) | ˂ 5 members | 76 | 63 | 139 | 34.5771 | 0.003 | 0.954 |
| 6 ≥ members | 143 | 120 | 262 | 65.1741 | |||
Source: Authors 2021
*Significance at 10%
**Significance at 5%
***Significance at 1%
Abbreviations: n Total Frequency, % Percentage, χ2 Chi Square Test, apple People
Impact of Covid-19 on income earnings (Income changes due to Covid-19) among VSLAs members
| Before Covid-19 | 63 | 201 | 138 | 2.19 | 0.7 | 103.705 | . | |
| During Covid-19 | 137 | 145 | 120 | 1.96 | 0.8 | 101.780 | . | |
| Frequency (n) | 74 | -56 | -18 | |||||
| Percentage (%) | 54.01 | -38.62 | -15 | |||||
Source: Authors 2021
Changes means changes from (Before to During period of Covid-19) calculated as in frequency (n) and percentage (%)
Significant at the 5% level of significance
(One Way ANOVA). 1 USD = MK811.37
Fig. 2Impacts of Covid-19 on Households Income of VSLAs Members. Source: Authors 2021
Predictors of the certainty of the future and sustainability of VSLAs during Covid-19 using by Binary Logistic Regression Model
| Variables | β | OR | 95% C. I |
|---|---|---|---|
| Gender of the respondent (1) | 0.437(0.094) | 1.548 | [0.928;2.582] |
| Age group (1) | 1.317(0.000) | 3.732 | [2.316;6.012] |
| Occupation (1) | -0.453(0.106)* | 0.636 | [0.367;1.101] |
| Education Level (1) | 2.181(0.047) | 8.852 | [1.033;75.888] |
| Are you head of the house (1) | -0.002(0.994) | 0.998 | [0.6;1.658] |
| Number of people in the house (1) | -0.174(0.481) | 0.84 | [0.518;1.363] |
| Shares contribution not on Time | 1.035(0.008) | 0.355 | [0.166;0.759] |
| Frequency of loans obtaining increasing | -0.507(0.049) | 0.602 | [0.364;0.998] |
| Loan Repayment not on time | -0.368(0.372) | 0.692 | [0.309;1.553] |
| Meetings | 0.572(0.021) | 1.773 | [1.09;2.881] |
| Constant | -1.506(0.211) | 0.222 | |
| Model Predicted Success | 68.10% | ||
| Log-likelihood ratio | 465.102 | ||
| Hosmer and Lemeshow Test | (df = 8) significance test result 8.469 ( | ||
| Omnibus Tests of Model Coefficients | (df = 10) significance test result 87.387 ( | ||
| Cox and Snell R2 | 0.196*** | ||
| Negelkerke R2 | 0.262*** | ||
| Sample Number (n) | 420 | ||
Source; Authors 2021
Abbreviation: OR Odds Ratios
(1): Reference Category using/based on Table 2 coding specifications
*Significance at 10%
**Significance at 5%
***Significance at 1%