Anne Kinsella

Disability on Irish Farms—A Real Concern

ABSTRACT Farmers operate within hazardous environments while conducting their day-to-day tasks, potentially resulting in injury or disability. Disability can serve as a major life-changing event for the farmer, the farm family, and the farm business. In Ireland, the agricultural sector reported the highest incidence of disability, yet there is relatively little known on the impact of agricultural-based disability. In 2007, a questionnaire was appended to the Teagasc (Irish Agricultural and Food Development Authority) National Farm Survey to obtain some metric of the prevalence and impact of disability on Irish farms, in addition to quantifying service/support requirements of farm operators experiencing disability. Almost 5.9% (∼6611) of Irish farm operators reported disability, primarily caused through illness/disease. Arthritis (31.4%), back problems (17%), and heart circulatory problems (12.5%) were most frequently reported. The lowest prevalence of disability was found among tillage (1.4%) and dairy (4.1%) farms, with the highest prevalence among cattle farms (7.1%). Family farm income was lower on disability-experiencing farms relative to nondisability farms (€123 per hectare), with a lower participation in off-farm employment also identified. Many farm operators (∼20%) ceased off-farm employment following disability. Discontinuation of off-farm employment can further precipitate family farm income decline, but also place additional pressures on the farm business if quality services/supports are not available. The current provision of services/supports to farm operators experiencing disability is perceived largely insufficient across the entire service/support spectrum from when disability was first experienced through to retirement. Awareness and issues surrounding eligibility were the primary reasons for failing to avail of currently available service/supports.

The associations of management and demographic factors with technical, allocative and economic efficiency of Irish dairy farms

The phasing out of the European Union (EU) milk quota will create opportunities for producers to expand without the constraint of quota which has limited expansion since 1984. Therefore, it will be necessary for Irish dairy producers to become more competitive by increasing performance using the least amount of inputs per unit of output and maximizing the level of technical and economic efficiency. The objectives of the current study were to measure technical, allocative and economic efficiency, and to investigate the associations of key management, qualitative and demographic characteristics on efficiency. Efficiency scores were calculated using the non-parametric methodology data envelopment analysis (DEA). The DEA results showed that on average the sample of Irish dairy producers were not fully efficient in 2008 with technical, allocative and economic efficiency results under variable returns to scale (VRS) of 0·771, 0·740 and 0·571, respectively. In a second stage analysis, Tobit regressions were used to determine the associations of key variables with the technical, allocative and economic efficiency scores. The efficiency scores were included as dependent variables and the key independent variables were a variety of management and demographic variables. Mean calving date, number of grazing days, breeding season length, milk quality, discussion group membership and soil quality were all associated with technical and economic efficiency. Milk recording, use of artificial insemination (AI) and level of dairy specialization were associated with allocative and economic efficiency only. Age and age squared were the only significant demographic associations with the efficiency scores.

Work‐related musculoskeletal disorders among Irish farm operators

BACKGROUND To establish prevalence, risk factors, and impact of work-related musculoskeletal disorders (WMSDs) among farmers in Ireland. METHODS In summer 2009, a questionnaire was appended to the Teagasc (Irish Agricultural and Food Development Authority) National Farm Survey (n = 1,110) to obtain data on the prevalence, risk factors and impact of WMSDs amongst farm operators in Ireland. Data were collected by trained recorders and analyzed using chi-square tests, t-tests, Mann-Whitneys U-tests and logistic regression models. RESULTS The prevalence of WMSDs in the previous year was 9.4% (n = 103), with the most commonly affected body region being the low back 31% (n = 32). Nearly 60% (n = 57) of farmers reported missing at least a full days work as a consequence of their WMSD. Personal factors evaluated using binary regression analysis, were found not to influence whether or not a farmer experienced a WMSD. However, work-related factors such as larger European Size Units (ESUs, OR: 1.007, CI: 1.002-1.012), greater number of hectares farmed (OR: 2.501, CI: 1.208-4.920), higher income (OR: 1.859, CI: 1.088-3.177), dairy enterprise (OR: 1.734, CI: 1.081-2.781), and working on a full-time farm (OR: 2.156, CI: 1.399-3.321) increased the likelihood of experiencing a WMSD. Working on a full-time farm was the only factor found to independently predict WMSDs in the multiple regression analyses. CONCLUSIONS This study suggests that the prevalence of WMSDs can be reduced by the application of improved farm management practices. A more detailed examination of the risk factors associated with WMSDs is required to establish causality and develop effective interventions.

An assessment of bird species within Irish agricultural landscapes using the Field Boundary Evaluation and Grading System

Capsule The Field Boundary Evaluation and Grading System (FBEGS) is a useful predictor of bird populations found in field boundaries located in southeast Ireland. Aims To assess the potential of FBEGS to evaluate the ecological quality of field boundaries in agricultural ecosystems and as a tool for the measurement of bird populations within field boundaries. Methods Surveys of bird populations were made in selected field boundaries on 50 farms in southeast Ireland in winter and during the breeding season. FBEGS surveys were also carried out on field boundaries to assess ecological quality. glms were fitted to assess the utility of the FBEGS Index as a predictor of bird populations. Results The FBEGS Index was an effective predictor of bird populations in the breeding season, but had limited use in predicting bird populations in winter. Within the overall FBEGS Index, the Associated Features score was a good predictor for populations in both the winter and breeding seasons. In addition, the Boundary Structural score of the field boundary was also an accurate predictor of birds in the breeding season. Conclusion The FBEGS Index has high potential for predicting the effect that changes in the farmed landscape will have on bird populations.