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Table 3 Results for 1st research question

From: What are the non-food impacts of GM crop cultivation on farmers’ health?

Coding 1 2 3 4 6 7 9
ID of the form Huang et al. (2005) Huang et al. (2002) Kouser and Qaim (2011) Kouser and Qaim (2013) Dev and Rao (2007) Bennett et al. (2006) Liu (2008)
Bibliographic reference (main article) J Huang, R Hu, S Rozelle, C Pray (2005). Insect-resistant GM rice in farmers’ fields: Assessing productivity and health effects in China. Science 308(5722): 688–690 J Huang, R Hu, C Fan, CE Pray, S Rozelle (2002). Bt cotton benefits, costs, and impacts in China. AgBioForum 5(4): 153–166 S Kouser, M Qaim (2011). Impact of Bt cotton on pesticide poisoning in smallholder agriculture: A panel data analysis. Ecological Economics 70(11): 2105–2113 S Kouser, M Qaim (2013). Valuing financial, health, and environmental benefits of Bt cotton in Pakistan. Agricultural Economics 44(3): 323–335 MS Dev, NC Rao (2007). Socio-economic impact of Bt cotton. Monograph No. 3. Hyderabad: Centre for Economic and Social Studies (CESS) R Bennett, S Morse, Y Ismael (2006). The economic impact of genetically modified cotton on South African smallholders: Yield, profit and health effects. The Journal of Development Studies 42(4): 662–677 EM Liu (2008). Essays on development economics in China. PhD thesis, Princeton University, New Jersey, USA
Country/ region China/Hubei province and Fujian province; preproduction trials China/In 1999—Hebei and Shandong. In 2000, Henan. In 2001, Anhui and Jiangsu provinces were added India/ Maharashtra, Karnataka, Andhra Pradesh, and Tamil Nadu in central and Southern India Pakistan/ Punjab Province, the leading cotton production province India/ Districts of Warangal, Nalgonda, Guntur and Kurnool in Andhra Pradesh are selected to represent the four agro-climatic zones South Africa/ Makhathini Flats China/ Henan, Shandong, Hebei and Anhui provinces
Methodology Survey, 2 years, counties involved in pre-production trials; farmers selected sometimes randomly sometimes not (some villages had a low number of adopters so all were selected); the survey allegedly has no drop-outs but only 69 households were interviewed in both years (77 households in the first year and 101 in the second); regression analysis to establish the effect of confounding variables Survey, 3 years; counties selected based on the cultivation of Bt cotton, villages and farmers selected randomly; some farmers were later dropped from survey (non-GM adopters become GM adopters); econometric model to verify the survey results Panel survey, 4 years; 4 states chosen, randomly choosing districts, villages, and households; attrition occurred, yet sample balanced, then checked if any bias was incurred; fixed-effects Poison regression model for pesticide poisoning incidence and fixed-effects linear regression model for pesticide use Survey, 1 year; districts chosen, but tehsils, villages and farmers randomly selected Survey, 1 year; districts, counties, villages and farmers selected randomly based on the area cultivated with cotton/Bt cotton, samples selected to be representative of the population; Archival data (time series records) for 3 years and in-depth interviews. An element of triangulation between primary and secondary data sources. The primary data came from Vunisa records held over 3 years which the company itself had not analysed for farm-level trends.
The primary data came from an in-depth survey of 32 farmers (selected randomly from a farmer organisation) combined with field measurement and observation
Survey, 1 year; Four provinces (Henan, Shandong, Hebei, and Anhui) that have the same cotton growing season (April to October) and have high Bt cotton adoption rates were selected; randomly selected two counties per province and two villages per county. In each village, twenty households were selected randomly and surveyed
Intermediary outcomes Sprayings: 0.5 vs. 3.7 (GM vs. non-GM); amount of pesticides (kg/season/ha) GM farmers: 2.0 kg/ non-adopters 21.2 kg Sprayings: 6.6 vs. 19.8 (Partial information, only for 1999, provided in Huang 2002, Science). As Bt cotton reduced pesticide use by 35.7 kg per hectare, or a reduction of 55% of pesticide use in the entire sample between 1999 and 2001. High variation between provinces Sprayings: 1.52 vs. 2.22 (GM vs. non-GM); In all four seasons, lower quantities of pesticides were used on Bt than on non-Bt plots. Bt crop-using farmers reduce pesticides mostly in the most toxic hazard category I pesticides (1.1 kg per acre is equivalent to a 70% reduction) Sprayings: 6 vs. 7 (GM vs. non-GM). Farmers use significantly lower pesticide quantities on Bt than on non-Bt plots. Still the reduction is less than in India or China Sprayings: 9 vs. 12 (GM vs. non-GM). Decreased by 18%; spraying pesticides either as a precautionary measure or on noticing pest without any regard to the economic threshold levels of the pest With the Bt variety farmers reduced the sprayings by 3 on average. Adopters also used less insecticide (bollworm and non-bollworm) especially in seasons 1 and 3, than non-adopters. Pesticide use was reported to costs not amounts All else equal, the average Bt cotton farmer reduced the use of pesticides by 19.5 kg/ha, or 73.3 percent, on his Bt plot compared with his non-Bt plot
Final outcomes 0 for full adopters; both insect-resistant GM and non-GM plots, 7.7% (2002) and 10.9% (2003) reported health problems. Only non-GM varieties: 8.3% (2002) and 3% (2003) had health problems 5% (1999), 7% (2000), and 8% (2001) for full adopters. 11% (1999), 19% (2000) and 10% (2001) for both types of plots. 22% (1999), 29% (2000) and 12% (2001) for non-adopters On average, only 0.19 poisoning cases per cotton season were reported by Bt farmers, as compared to 1.60 cases by non-Bt farmers 1.42 (Bt) vs 1.96 (non-Bt) average number of poisonings 25% (Bt cotton) vs 27% (non-Bt) number of poisonings When the number of adoptions of Bt cotton increases, the number of poisonings decrease (logarithm of the number of hospital admissions due to pesticide poisoning, as a function of adoption of Bt cotton). The previous article on the same study (2003) shows that in the first year of adoption (0.1% Bt cotton adoption) there were 20 poisonings registered for the peak month of February. Four seasons later, at 60% adoption rate for Bt cotton, in February, there were 4 cases of poisonings 30% (129) of farmers reported that they experienced at least one symptom since 1996, but it is not reported to the cultivation of Bt cotton
Main sources of bias 1. farmer recall was used, although farmers were interviewed about recent data (same season); 2. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects; 3. attrition was not dealt with, although it obviously occurred (out of 77 households in the first year, only 69 remained in the second) 1. farmer recall was used, although farmers were interviewed about recent data (same season); 2. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects; 3. differences between GM and non-GM farmers were not analysed 1. farmer recall was used, although farmers were interviewed about recent data (same season); 2. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects; 3. differences between GM and non-GM farmers were not analysed 1. farmer recall was used, although farmers were interviewed about recent data (same season); 2. only one year survey; 3. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects (it was stated as a general observation that farmers do not use protective measures, but the farmers interviewed were not asked about such measures) 1. farmer recall was used but at least 2 years after the cultivation (the limits of the farmers recollection is stated as one of the limits of the study); 2. only 1 year survey; 3. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects 1. only one area studied. 2. the written records which form the majority of the data were not selected randomly 1. farmer recall was used but at least 2 years after the cultivation (the limits of the farmers recollection is stated as one of the limits of the study); 2. only 1 year survey; 3. personal protective measures for pesticide applications as confounding variables were not analysed to connect GM cultivation and health effects; 3. differences between GM and non-GM farmers were not analysed
Other comments Institutional conditions such as subsidies, extension services, price controls were registered as general background but their impact on the results has not been assessed The only study that registers the types of pesticides used. The season 2000–2001 shows a marked decrease in pesticide poisoning for non-GM users and farmers with both GM and non-GM plots. This finding is left unexplained Although having a quite good random selection (except for state level) the authors also control for non-random selection bias. The paper points out that hired labourers might reduce the reporting of poisonings. The correlation between Bt adoption and reduction on number of poisonings is strong for full adopters and insignificant for partial ones. Also, the effect of Bt cotton adoption on poisonings is significant only after a few years of cultivation (authors hypothesize it to be due to a suppression of bollworm infestation following a widespread adoption of Bt cotton) Authors control for self-selection bias by verifying the results on the sub-sample of partial adopters. No statistical correlation was performed between pesticide amounts and poisonings. It was a reduction in the pesticides used but not as much as in China or India (authors suppose it was due to a higher pressure of sucking pests or lack of experience with the technology) No statistical correlation was performed between pesticide amounts and poisonings. The poisonings are reported as “health problems at the time of the spray”. Whether or not they are correlated with the pesticide use, it is not stated. In fact, the study does not have any comment about the health effects of pesticide use. An important confounding variable is the rainfall: during the studies year it was 33% less than normal The possibility for a self-selecting bias was eliminated through a cohort study research. No systematic bias due to loss of written records by Vunisa (data was validated). For the number of pesticide poisonings, there was no comparison between Bt and non-Bt adopters. It looks like that the authors attempted to bring only circumstantial evidence between Bt adoption and health benefits It points toward another possibly determinant affecting the impact of GM crops cultivation: spurious seeds. Liu focuses very well on some issues like pest pressure but completely ignores other such as irrigation and the reasons for returning to conventional cotton cultivation.
Dealing with selection bias: the 1st chapter of the dissertation focuses on what determined the adoption of Bt cotton. Data on health effects has no details: impossible to say if the number of poisonings are connected to Bt cultivation