Effect of livelihood diversification on arable crop farmers' household wellbeing in Southwestern, Nigeria

Introduction

Agriculture remains a key livelihood activity in Southwestern Nigeria, where arable crop farming supports food production, employment, and household income. However, the sustainability of smallholder farming systems has been increasingly constrained by land degradation, climate variability, rising input costs, insecurity, and limited access to modern agricultural support services. These challenges have reduced farm productivity and increased income instability, thereby affecting household wellbeing. Within the Sustainable Livelihoods Framework, rural households operate under a vulnerability context and rely on available livelihood assets to pursue strategies that enhance welfare outcomes. In this regard, livelihood diversification has become a major adaptive strategy. It involves engagement in multiple income-generating activities across farm and non-farm sectors to reduce risk, stabilize income, and improve welfare outcomes. In Southwestern Nigeria, arable crop farmers commonly combine farming with petty trading, wage labour, artisanal work, transport services, and small-scale enterprises as coping mechanisms against agricultural uncertainty (Adeomi, Fadoju, Oseni and Ogunya, 2022) [2] .

Empirical studies show that socioeconomic characteristics such as age, education, household size, farm size, and access to credit significantly influence participation in livelihood diversification, with implications for household welfare outcomes (Chinalurum et al., 2024) [4] . Similarly, diversification has been associated with improved income stability, resilience, and food security among rural households in Southwestern Nigeria (Olawuyi & Olawuyi, 2022) [11] . Household wellbeing in this study refers to multidimensional welfare outcomes, including income stability, food security, health status, educational attainment, asset ownership, and access to basic services, as well as the capacity to cope with shocks and maintain living standards over time. However, the welfare effects of livelihood diversification vary across households depending on the type of activities undertaken and resource endowment. While some households experience significant welfare improvements, others remain engaged in low-return activities with limited impact on wellbeing. Existing studies have largely focused on determinants or income effects, with limited integrated evidence on how diversification influences multidimensional household wellbeing among arable crop farmers in Southwestern Nigeria. www.extensionjournal.com Against this background, this study examines the effect of livelihood diversification on the household wellbeing of arable crop farmers in Southwestern Nigeria. Specifically, it describes the socioeconomic characteristics of respondents, identifies diversification activities, assesses their impact on household wellbeing, and examines the constraints associated with diversification. In line with the research objectives, the study further tests the following null hypotheses:  H₀₁: There is no significant relationship between selected socioeconomic characteristics and the effect of livelihood diversification on the household wellbeing of arable crop farmers in the study area.  H₀₂: There is no significant relationship between the challenges associated with livelihood diversification and the effect of livelihood diversification on the household wellbeing of arable crop farmers in the study area.

Methodology

The study was conducted in Southwestern Nigeria, a region characterized by a tropical climate with distinct wet and dry seasons and suitable for the cultivation of major arable crops such as maize, cassava, yam, okra, and vegetables. The target population comprised all arable crop farmers cultivating these crops within the region. A multistage sampling procedure was used to obtain a representative sample. Thirty percent of the states in Southwestern Nigeria were randomly selected, resulting in the inclusion of Ogun and Oyo States. Fifty percent of the Agricultural Development Programme (ADP) zones in each selected state were then randomly chosen, followed by 25% of blocks within the selected zones and 50% of cells within the selected blocks. From the 235 farmer groups identified across the selected cells, 20% (47 groups) were randomly selected. Finally, 20% of registered farmers in each selected group were sampled, yielding a total of 281 respondents. Primary data were collected using a structured interview schedule that captured socioeconomic characteristics, livelihood diversification activities, factors influencing diversification, perceived effects on household wellbeing, and challenges associated with diversification. Socioeconomic variables such as age, sex, marital status, education, household size, farm size, farming experience, and income were measured using natural units and categorical classifications. Participation in diversification activities was recorded using binary responses, while factors influencing diversification and the associated challenges were measured using a two-point and a three-point scale respectively. Perceived effects on household wellbeing were assessed using a five-point Likert scale, and challenges were measured using a three-point severity scale. Weighted mean scores were computed to rank factors, effects, and challenges. Data were analyzed using descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics, including Chi-square tests and Pearson Product Moment Correlation (PPMC), with significance set at p ≤ 0.05. Although the study assessed household wellbeing using perception-based Likert items, this approach is widely accepted in contemporary livelihood and wellbeing research, particularly where multidimensional welfare outcomes include subjective and experiential components (Tessema & Simane, 2020; Nguyen & Nguyen, 2022) [9,13] . The study strengthened these subjective measures by incorporating objective socioeconomic indicators such as income, household size, farm size, and farming experience into the correlation analysis. While self-report bias and endogeneity are inherent limitations of cross-sectional perception studies, the analytical framework adopted here is appropriate for exploratory research aimed at identifying significant associations rather than establishing causality (Alemu, 2023; Habib et al., 2023) [7,3] . These limitations are acknowledged, and future studies are encouraged to employ longitudinal data or econometric models to better isolate causal effects.

Socio-economic characteristics of the respondents

Results in Table 1 show the socio-economic characteristics of the respondents. The result shows that arable crop farming in Southwestern Nigeria is dominated by middleaged respondents, with a mean age of 45.5 years, suggesting a relatively active but ageing farming population. This age structure implies a strong need for income stability, which supports engagement in livelihood diversification, as also noted by Olawuyi and Olawuyi (2022) [11] . The overwhelming dominance of males (96.80%) reflects the gendered nature of arable crop farming and suggests limited female participation in primary farming activities, although women may still engage more in non-farm income activities. Household sizes are relatively large (mean = 8), indicating availability of family labour but also higher consumption pressure, which often drives diversification decisions, consistent with Chinalurum, Ojoko, and Junaidu (2024) [4] . Low educational attainment (over 80% with no or primary education) suggests restricted access to high-return non-farm employment, pushing households toward informal activities such as trading and artisan work. This pattern is consistent with Adeomi et al. (2022) [2] . Income levels are generally low (mean ₦46,450), indicating economic vulnerability and reinforcing the need for livelihood diversification as a coping strategy, as also observed by Adeniyi, Ademola, Alabi, and Busari (2023) [1] . The findings suggest that livelihood diversification in the study area is largely driven by economic necessity rather than opportunity, with most households engaging in low-return informal activities that may have limited effects on longterm welfare improvement. These findings imply that arable crop farmers are primarily "push-diversified," meaning that diversification is induced more by necessity than opportunity. This aligns with the Sustainable Livelihood Framework, which posits that households diversify income sources as a response to shocks, seasonality, and structural constraints to stabilize consumption and reduce vulnerability. This interpretation is strongly supported by recent empirical evidence from Nigeria. For instance, Onuwa et al. (2022) [12] found that livelihood diversification among rural farmers in Plateau State is significantly influenced by socioeconomic constraints and vulnerability conditions, concluding that diversification is largely a response to limited farm productivity and structural rural challenges rather than voluntary economic expansion. In addition, Olawuyi and Olawuyi (2022) [11] established that livelihood diversification in South-West Nigeria serves as a riskbuffering mechanism against climatic, economic, and institutional shocks, thereby enhancing household resilience under unstable agricultural conditions. Source: Field survey, 2026 www.extensionjournal.com

Table 3: Effects of livelihood diversification on arable crop farmers

The weighted mean scores (WMS) show the extent to which livelihood diversification impacts household wellbeing, with higher values indicating stronger positive effects. The highest-ranked impact, stable income (x̄ = 3.44), implies that livelihood diversification plays a major role in income smoothing and reducing vulnerability to shocks. This suggests that engaging in multiple activities helps farmers cope with seasonal fluctuations and uncertainties in agriculture. This finding agrees with Alemu (2023) [3] , who found that diversification significantly improves income stability and overall household welfare. The relatively high WMS for improved social status (3.22) and reduced ruralurban migration (3.16) indicates that diversification enhances social recognition and reduces the need for migration by creating alternative income opportunities locally. This implies that diversification contributes to rural retention and community stability. Similarly, Habib et al.

(2023) [7] noted that diversified livelihoods strengthen social capital and reduce economic pressures that drive migration. The WMS values for improved lifestyle (3.15), social networks (3.15), and social mobility (3.14) suggest moderate positive effects on living standards and social wellbeing. This implies that diversification not only improves income but also enhances household consumption, relationships, and opportunities for advancement. This is consistent with Kassegn and Abdinasir (2023) [8] , who reported that livelihood diversification improves both economic and social dimensions of wellbeing. [11] , who reported that rural households in Southwestern Nigeria diversify mainly into informal non-farm activities as a coping strategy to manage income shocks and food insecurity. Similarly, the prominence of trading, artisanal work, and transportationrelated activities reflects the tendency of rural households to engage in labour-intensive and small-scale enterprises that require minimal capital investment. This supports the findings of Adeomi et al (2022) [2] , who observed that livelihood diversification among rural farming households is largely shaped by limited access to productive capital and is concentrated in low-return informal sector activities. The www.extensionjournal.com findings imply that although livelihood diversification is widely practiced among arable crop farmers in the study area, it is predominantly survival-oriented rather than investment-driven. 5 show the challenges associated with livelihood diversification on arable crop farmers. The weighted mean scores show that limited access to education (WMS = 2.89) and inadequate capital (WMS = 2.65) are the most serious constraints, implying that lack of skills and financial resources strongly limit effective livelihood diversification. This supports findings by Habib et al. (2023, who reported that human and financial capital are critical determinants of successful diversification in rural households. The relatively high WMS for insecurity (2.52) [7] and limited access to information and technology (2.43) suggests that environmental and institutional barriers also restrict diversification opportunities, indicating that farmers operate under risky and poorly supported conditions.

Similarly, Kassegn and Abdinasir (2023) [8] found that lack of access to information, infrastructure, and secure environments reduces the ability of farmers to diversify into more productive activities. Moderate WMS values for health challenges (2.42) and lack of entrepreneurial skills (2.29) imply that poor health and low business capacity further limit income diversification, keeping farmers in lowreturn activities. This aligns with Alemu (2023) [3] , who noted that skills and labour efficiency significantly influence the benefits derived from diversification. However, the lower WMS for policy barriers (1.55), cultural norms (1.52), and market access (1.45) indicates that these are perceived as less critical constraints compared to resource-based challenges, suggesting that internal household limitations are more binding than external factors.

Test of hypotheses

The hypotheses of the study stated in a null form were tested and the results are presented below. HO1: There is no significant relationship between selected socioeconomic characteristics and the effect of livelihood diversification on arable crop farmers' household wellbeing in the study area. The test of the significant relationship between selected socioeconomic characteristics and the effect of livelihood diversification on arable crop farmers' household wellbeing in the study area were presented in Table 6. Socio-economic factors (age, household size, income, farm size, and farming experience) of the respondents show a positive and significant influence (p<0.05) on livelihood diversification among farmers. Income (r = 0.411) has the strongest effect, indicating that better-off households diversify more due to greater investment capacity, which agrees with recent findings that income strongly drives diversification intensity (Alemu, 2023) [3] . Household size (r = 0.283) also plays an important role by providing labour for multiple activities, consistent with evidence that larger households diversify more (Kassegn & Abdinasir, 2023) [8] . Additionally, age (r = 0.241) and farming experience (r = 0.227) suggest that older and more experienced farmers are more likely to diversify due to better knowledge and risk management, while farm size (r = 0.207) indicates that access to land supports diversification. www.extensionjournal.com Source: Data analysis, 2026. S = Significant; NS = Not Significant H02: There is no significant relationship between the challenges associated with livelihood diversification on arable crop farmers' households and the effect of livelihood diversification on arable crop farmers' household wellbeing in the study area.

The test of the significant relationship between the challenges associated with livelihood diversification and the perceived effects of livelihood diversification on arable crop farmer's households was presented in Table 7. Pearson Correlation analysis revealed a positive and significant relationship (r = 0.305, p = 0.001) between the challenges and the perceived effects of livelihood diversification. This implies that as challenges increase, they significantly influence (and often limit) the outcomes of diversification on household wellbeing. The correlation (r = 0.305) suggests that constraints such as lack of capital, poor access to resources, and insecurity shape how effective diversification can be. This supports findings by Alemu (2023) [3] that the benefits of livelihood diversification depend on the level of constraints faced by households. Similarly, Habib et al. (2023) [7] emphasize that livelihood outcomes are strongly affected by limitations in human, financial, and institutional assets.

Conclusion and Recommendations

The study established that livelihood diversification significantly contributes to the wellbeing of arable crop farmers' households in Southwestern Nigeria. Farmers engaged in various non-farm and off-farm activities mainly as a response to climate variability, crop failure, low farm income, and limited market opportunities. Livelihood diversification improved household income stability, social status, lifestyle, and reduced rural-urban migration. However, most diversification activities were concentrated in low-return and informal ventures, indicating that diversification among rural households is largely necessitydriven. The study further revealed that socioeconomic characteristics such as age, income, household size, farm size, and farming experience significantly influenced livelihood diversification, while challenges including inadequate capital, limited access to education, insecurity, and poor access to information and technology constrained its effectiveness.

The study therefore recommends that government and relevant stakeholders should strengthen rural financial support systems through accessible credit facilities and investment programmes for farmers. Extension and capacity-building services should also be enhanced to improve farmers' entrepreneurial and technical skills for more profitable livelihood activities. In addition, improving rural infrastructure, market access, and climate adaptation support will enhance the sustainability and effectiveness of livelihood diversification strategies among arable crop farmers.

References

1. Adeniyi KMI, Ademola HA, Alabi AA, Busari AO. Livelihood diversification among arable crop farmers in Osun State, Nigeria. Uniosun J Agric Renew Resour. 2023;7(1):1-18.
2. Adeomi DT, Fadoju DT, Oseni RO, Ogunya L. Socioeconomic factors influencing livelihood diversification among rural farming households in Southwest Nigeria: A fractional response model approach. Sci Pap Ser Manag Econ Eng Agric Rural Dev. 2022;22(4):21-30.
3. Alemu FM. Measuring the intensity of rural livelihood diversification and its impact on household welfare. MethodsX. 2023;10(1):102191.
4. Chinalurum CA, Ojoko EA, Junaidu M. Determinants of livelihood diversification among farming households in Nigeria. J Agripreneursh Sustain Dev. 2024;7(2):7885.
5. Chukwu NO, Chukwu JO. Drivers of households' offthe-farm income diversification patterns in Nigeria. Margin J Appl Econ Res. 2023;28(4).
6. Duale MM. Challenges and opportunities of livelihood diversification in Ethiopia. Int J Agric Econ. 2024;9(3):134-147.
7. Habib N, Ariyawardana A, Aziz AA. The influence and impact of livelihood capitals on livelihood diversification strategies in developing countries: A systematic review. Environ Sci Pollut Res. 2023;30(27):1-17.
8. Kassegn A, Abdinasir U. Determinants of rural households' livelihood diversification strategies: In the case of North Wollo Zone, Amhara National Regional State Ethiopia. Cogent Econ Finance. 2023;11(1).
9. Nguyen TT, Nguyen HT. Subjective wellbeing and livelihood strategies among rural households in Vietnam. Soc Indic Res. 2022;160(2):589-610.
10. Ojo OA, Olarinoye EB, Ojo MA. Effects of livelihood diversification on poverty status of rural farming households in Kwara State, Nigeria. J Agric Rural Dev Trop Subtrop. 2024;125(2):185-195.
11. Olawuyi SO, Olawuyi TD. Livelihood diversification and farmers' well-being: Lessons from South-West, Nigeria. J Dev Areas. 2022;56(4):231-246.
12. Onuwa OC, Musa Y, Duniya M. Socioeconomic determinants of livelihood diversification among rural farming households in Plateau State, Nigeria. Agric Soc Econ J. 2022;22(4):301-309.
13. Tessema YA, Simane B. Livelihood resilience and subjective wellbeing: Evidence from rural Ethiopia. J Rural Stud. 2020;76:234-243.