Measurement and Spatial Differentiation of Farmers' Livelihood Resilience Under the COVID-19 Epidemic Outbreak in Rural China

Strengthening oil palm smallholder farmers' resilience to future industrial challenges

Oil palm cultivation has improved living standards and alleviated the poverty of many smallholder farmers. However, challenges such as climate change, aging palms and negative sentiments in the major markets, threaten the wellbeing of and raise the question on smallholder farmers' resilience, which remains poorly understood. Using primary data from Indonesia, the largest palm oil producer in the world, we measure and evaluate the resilience of oil palm smallholder farmers using the Sustainable Livelihoods Approach. Our results revealed five classes of smallholders with different levels of resilience: vulnerable, economically and socially constrained, low-skilled, semi-secure and adaptive smallholders. The farmers in the least resilient group are majorly older local farmers, who established oil palm plantations independently. Meanwhile, the most resilient group is dominated by smallholders who participated in the migration program, and in the past, received support from the government to start oil palm plantations. Our study highlights the heterogeneity of smallholders' livelihood resilience and the need for inclusive and tailored interventions for the various classes of smallholder farmers to establish sustainable communities.

Potential factors associated with resilience among older adults in rural China: a multilevel analysis

BACKGROUND

Resilience is crucial for older adults who experience adversities, but research on the issue in rural China remains limited. This study aims to examine factors associated with resilience among older adults in rural China, as related to different types of resilience, and under different levels of adversity.

METHODS

Data were taken from the eight-wave (2001-2021) Longitudinal Study of Older Adults in Anhui Province, China. We used data from the eighth wave (2021) for the outcome variables and lagged predictors (2018) to avoid reverse causal effects. The study sample included individuals 60 years and above, excluding new participants from 2021, those without any adverse events, and any respondents with incomplete analytic data. Resilience was operationalized as residuals of the regressions of life satisfaction (Life Satisfaction Scale) and depressive symptoms (CES-D) on adversity, referred to as Type-1 and Type-2 resilience respectively. These two types of resilience were then treated as the outcome variables in subsequent multilevel regressions, with the predictors focusing on individual, social, and environmental characteristics and resources. This study adheres to STROBE guidelines.

RESULTS

43% of rural older adults exhibited both Type-1 and Type-2 resilience, whereas 18% exhibited only Type-1 resilience and 7% exhibited only Type-2 resilience. Common factors associated with both types of resilience included self-rated health, satisfaction with one's own financial situation, and the prestigiousness of social networks. Predictors for higher levels of Type-1 resilience included higher levels of financial and emotional support and more options for places of leisure. Predictors for higher levels of Type-2 resilience included greater access to medical care. The prestigiousness of social networks, higher levels of emotional support and instrumental support, access to medical care, and more options of places of leisure were positively associated with resilience in the low-adversity group (first tertile of adversity), only satisfaction with financial situation was positively correlated with the resilience of the middle-adversity group (second tertile), while better self-rated health, satisfaction with financial situation, and financial support yielded greater resilience in the high-adversity group (third tertile).

CONCLUSIONS

We examined two types of resilience among older adults in rural China, and found that they have shared and unique associated factors. In addition, the potential factors influencing resilience varied with the level of adversity.