PEN Report Pesticide Use in Vietnam Mar2005

8/3/2019 PEN Report Pesticide Use in Vietnam Mar2005

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farmers in four provinces in the South, found 96.6% of farmers used pesticides excessively andnot in compliance with the instructions on the labels, and nearly 95% of farmers pour residualspray into canals and ditches or reapply on other plants or over-apply on the same crop just toget rid of it (Huan et al., 2000). In regards to the health impacts of pesticide use, hospitaladmission records in Vietnam trace nearly 11% of all poisonings to pesticide misuse: orapproximately 840 poisonings in 53 cities and provinces in 1999 (Poison Control Center, VietnamMinistry of Health, 2000).2

Given the rather dire picture of pesticide use in Vietnam, two broad questions that this section ofthe Poverty-Environment Nexus report attempts to answer are:

1) Are the poor using more, toxic pesticides?

2) Is pesticide use, and its attended health consequences, impacting the poor to a greater extentthan the non-poor?

In developing a response to these questions, the World Bank team constructed detailed pesticideuse and medical surveys to be implemented on a representative sample of poor and non-poorfarmers in Vietnam. A description of the survey, sample and the results follows.

II. DESCRIPTIONOFTHE WORLD BANKSURVEYANDSAMPLINGSTRATEGY

A survey of Vietnamese farmers was carried out by the Research Department of the World Bankin the winter of 2003. Structured questionnaires were used to collect information on farmingsystems, pesticide use and practices, applicator precautions/ averting behavior and health/environmental effects. The survey was divided into two major sections, one dealing with theeconomics of pesticide use (e.g. production, pesticides used, protection, training, etc) andanother strictly dealing with the health of the farmer (e.g. questions on self-reported healthailments/ health-related habits, a general physical exam, and patch-skin and blood tests forpesticides). The survey was constructed by the World Bank team in collaboration with theUniversity of Economics in Ho Chi Minh City 3(for the socio-economic portion of the survey) andthe Centre of Occupational and Environmental Health (COEH) of the Vietnam Association of

Occupational Health (VINOH) for the medical survey.4 Each of these World Bank counterpartswere responsible for the implementation of the survey. To minimize any possible reporting bias,the survey was conducted under the agreement that the team would not reveal the identity of thefarms surveyed or the respondents.

2 Reliable data on the incidence of pesticide poisoning is rare in most countries. At best it is anunderestimate because the source of the surveillance data from which these figures are derived is healthfacilities. These figures represent only a small fraction of pesticide poisoning for a number of reasons. First,only a small number of severe poisonings are present in the health care system. These usually are suicideattempts. The bulk of cases - milder, occupationally related - will not necessarily report to the health caresystem due to costs, inaccessibility of services, or fear of reporting and loss of employment. Finally, thosefew farmers that do present themselves for treatment are often misdiagnosed because pesticide poisoning

mimics other health problems. Therefore the magnitude of occupational pesticide poisoning isunderestimated which makes it difficult to inform policy (FAO, 2001).

The World Health Organization estimates that there are 50 cases of poisoning for every case reported andregistered, which translates into nearly 375,000 cases each year in developing countries. The estimatednumber of fatalities from agrochemical exposure are at least 20,000 every year, the majority in developingcountries (WHO, 1990; Kishi et al., 1995; Pimental et al., 1992; Rosenstock et al., 1991).3 The socio-economic portion of the study was headed by Professor Nguyen Huu Dung of the EnvironmentalEconomics Unit, University of Economics, Ho Chi Minh City.4 The medical portion of the survey was headed by Dr. Khuc Xuyen of the Vietnam National Association ofOccupational Health (VINOH).


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Although the survey was conducted in a single season (the winter of 2003), respondents wereasked detailed production and pesticide use questions that spanned the period of one year. Thusthe survey contained information for the three major growing seasons of Winter-Spring 2002-2003, Spring-Summer 2003, and Summer-Autumn 2003.

IIA

) DEFINITION

OF

THE

POOR

As the primary focus of the study was to investigate the potential inter-linkages of pesticide useand the poor, we adopted the poverty line set by the Ministry of Labor, Invalids, and Social Affairs(MOLISA) Decision No. 1143 (MOLISA, 2001). This poverty line was also re-iterated in therecent Comprehensive Poverty Reduction and Growth Strategy (CPRGS) signed by thegovernment in 2002.5 Applying this criteria to our sample of farmers, Table 1 presents thenumber of respondents who fell into the category henceforth known as the poor.

Table 1: Sample poverty distribution6

Poverty classification Number Percent

Poor ( 1,200,000 VND/year) 79 13.1

Non-poor 524 86.9

Total 603 100.0

II B) GEOGRAPHICALLOCATIONOFTHESAMPLE

The main geographical area of interest is the Mekong Delta since it has been identified as themost intensive with respect to production and pesticide use (see Map 1 for details). As asampling strategy, the team took the following into consideration when selecting candidatedistricts and communes: 1) identifying areas where the poor versus non-poor comparison wouldbe possible (via the use of the latest poverty map from the World Bank, 2003); 2) areas whererice production is dominant; 3) selection of farms that vary in geographical location (e.g. coastalversus inland farms); and 4) focus on rural areas so as to target the rural poor (as opposed to theurban poor in the cities).

5 The new poverty line published in 2001 is to be applied to poverty measurement in the 2001-2005 period in

which the new national poverty line developed by the National Poverty Reduction Program is defined atdifferent levels depending on specific areas/regions, based on per capita income: VND 80,000 per month forisland areas and rural mountainous areas, VND 100,000 per month for rural plain areas, and VND 150,000per month in urban areas (pg. 17, CPRGS, 2002).6 The low representation of poor farming households is primarily due to the definition of poor (as 1,200,000

VND/ year); where the majority of farms exceed this poverty line where many of the poor do not own landand thus do not make pesticide decisions (the primary focus of the survey).


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Map 1: District location and number of poor/non-poor farms in the survey sample

Note: the low representation of poor farming households is primarily due to the definition of poor (as 1,200,000 VND/ year); where the majority of farms exceedthis poverty line since many of the poor do not own land and thus do not make pesticide decisions (the primary focus of the survey).


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III. SURVEY RESULTS

III A) GENERALFARMERSTATISTICS

Table 2: Farmer characteristics (%).

Ownership Poor Non-poor Farm size Poor Non-poor Education Poor Non-poor

Own < 100% of land 5.1 3.8 < 0.50 ha 36.7 9.4 No schooling 1.3 1.3Own 100% of land 94.9 96.2 0.50-0.99 31.6 26.3 Primary 54.4 32.1

Total 100.0 100.0 1.00-1.49 20.3 23.7 Secondary 34.2 45.8

1.50-1.99 6.3 17.2 High school 7.6 18.7

2.00-2.49 1.3 8.6 Other 2.5 2.1

2.50+ 3.8 14.9 Total 100.0 100.0

Total 100.0 100.0

Sample size (n=) 79 524 79 524 79 524

A large proportion of the farmers surveyed owned 100% of their land, with 89% of poor and 60%of the non-poor farming less than 1.5 hectares of land. In terms of education, over half of thepoor had at least primary education, while a larger percentage of the non-poor had secondary

and high school education.

III B) PESTICIDE USE

Pesticide use is generally measured using a variety of key indicators such as number ofapplications, the absolute amount used, as well as a measure of the relative risk of the pesticide.The absolute measures of pesticide quantity are straightforward in interpretation, however,factoring in the relative risk of each pesticide requires the adoption of a methodology that canrank one pesticide as more toxic than another. The methodology we propose is elaboratedbelow.

By simply summing all pesticides (measured as kg of active ingredient) used in crop production,this implicitly assumes that all pesticides are alike in terms of their toxicity. However, it iscommon knowledge that different substances have different levels of toxicity to both humans andthe environment. To do this, we constructed risk-weightedmeasures by defining risk as therelative toxicity or lethality of each active ingredient. Risk-weighted measures place a greaterweight on more toxic substances and provide a more convenient measure of comparing the useof one pesticide over another from a health-hazard perspective. To gauge the relative toxicity ofeach active ingredient, a measure called the LD50 (or lethal dose 50%) is used. LD50 is astatistical estimate of the number of milligrams (mg) of toxicant per kilogram (kg) of bodyweightrequired to kill 50% of a large population of test animals. Pesticides with a lower LD50 value aremore toxic, thus in the calculations used for this study, each pesticide load was multiplied by1/LD50 to account for its relative toxicity and giving greater weight to more toxic substances.


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Figure 1: Mean pesticide application, risk-weighted amountand number of applications by poor/non-poor (kg).

*** - difference is statistically significant at the 1% level;** - difference is statistically significant at the 5% level.

Returning to the pesticide use indicators in Figure 1, we see that the mean application amountover the three growing seasons is higher for the non-poor, as well as in terms of the number ofapplications. However, when we account for the relative risk of the pesticides used, the poor areusing more toxic pesticides in absolute terms.7

To better understand the extent of risk exposure, make use of a widely-known categorical methoddeveloped by the World Health Organization (WHO) and also based on the LD 50 measure.

8

Pesticides are divided into 4 major hazard groups: Category Ia & Ib (extremely hazardous),Category II (moderately hazardous), Category III (slightly hazardous), and Category U (leasthazardous or unlikely to present acute hazard under normal use). Field evidence suggests thathuman poisonings correlate reasonably well with these toxicity ratings (Levine and Davies, 1982).

In Table 3, we provide a summation of the total amounts of pesticides under the WHOclassification system. Note that over one-half of the pesticides under use in this sample aremoderately hazardous. In Figure 2 we see further evidence of the earlier result that the poor areusing more toxic pesticides by the higher mean use of WHO Ia & Ib pesticides.

Table 3: Total amount pesticides applied by WHO classification

Category Total (kg a.i.) Percent

Ia (extremely hazardous) 0.0 0.0

Ib (extremely) 5.4 0.5

II (moderately) 594.7 55.5

III (slightly) 187.3 17.5

U (Unlikely) 283.8 26.5

Total 1071.1 100.0

Figure 2: Mean application of WHO Ia & b

7 Mean application amounts on aper hectare basis (both un-weighted and risk-weighted) possess the samepattern where the non-poor applied at a higher per hectare rate and in terms of the risk-weighted measure,the poor registered a higher rate.8 The WHO toxicity rating is based on the lowest published oral LD 50, typically tested on rats. While WHO

ratings generally reflect acute toxicity, they also take into account other toxic effects such as reproductiveand developmental toxicity (WHO, 2002).

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Application amount ***

(kg)

Risk-weighted amount

(per 100 kg)

No. of applications **

Poor (n=79) Non-poor (n=524)


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and common pesticide classes by poor/non-poor9(kg).

*** - difference is statistically significant at the 1% level;

Yet another important method of classifying pesticides is by their chemical class. The chemicalclass is quite simply a pesticides chemical structure, which will dictate the properties that apesticide holds. Perhaps the two of the most important properties to human and environmentalhealth are toxicity and degradability. Certain chemical classes have been identified as beinghighly toxic and persistent in the environment. Epidemiological studies have linked so-calledcarbamates, organophosphates and pyrethroids with fetal death, hormonal changes, DNAdamage, birth defects, and abnormal sperm, ovaries and eggs.1011

Among the sample farmers in the Mekong Delta, we see a consistent pattern in Figure 2 amongthe non-poor, where they are using significantly higher average amounts of carbamates,organophosphates and pyrethroids. Once again we note in the first bar of Figure 2 that it is thepoor who are using the most toxic pesticides according to the WHO classification system. Thus

when setting priorities, one must first select a measure upon which a policy benchmark can beformulated. For example, if one was concerned with banning only WHO Ia & Ib pesticides, thenthe evidence suggests that focusing on poor farmers may better address this issue than strictlyfocusing on all farmers in general.

Figure 3: Mean application of insecticides, herbicides,

9 Similarly, on a per hectare basis, the poor applied a higher amount of WHO Ia & b pesticides.10

Organophosphates as a class of insecticides have been linked with Non-Hodgkins lymphoma, leukemia,and lung cancer. In children, organophosphates have been linked to aplastic anemia, which is the failure ofthe bone marrow to produce blood cells, and leukemia. Children with asthma may have severe reactions toorganophosphates in particular (Zahm et al., 1997).11

Repeated assaults to the nervous system from cholinesterase inhibitors (organophosphates and

carbamates) may lead to chronic polyneuropathies (damage to the brain). There are other groups such aspyrethroids and organochlorines that are suspected to alter hormonal balance and the reproductive systembecause such effects have been identified in animal populations. Given these potential long-term effects, itis important to monitor the use of these products and to inform those who use them of the potential hazardsthey may pose (FAO, 2001).

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

WHO Ia & Ib Carbamates Organophosphates

***

Pyrethroids ***

kilograms



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fungicides and others by poor/non-poor (kg).

*** - difference is statistically significant at the 1% level;

Pesticides can also be classified by their intended use, for example, the use of insecticides forinsect attacks, herbicides for weeds, and fungicides for the mitigation of plant mildew and root rot.Results of the survey reveal in Figure 3 that the non-poor use insecticides, herbicides andfungicides at a rate more than double that of the poor. These averages also closely coincide withthose of other studies of pesticide use in the Mekong Delta, where insecticides dominated thegroup averages (Dung and Dung, 2000).

Figure 4: Misuse of pesticides: Do farmers use any pesticides recommended for othercrops, on rice?

The misuse of pesticides, or using pesticides on a crop for which it is unintended, is not a verycommon practice among the farmers in the survey; although, nearly 5% of non-poor farmers

mentioned misuse of some kind.

12

These results also highlight the importance of confirming self-reported information in the field.

The overuse of pesticides is also a concern from health and environmental perspectives. In thesurvey farmers were asked their pesticide dosage rates which were then compared to therecommended dosages on the label. A statistical analysis of the extent of pesticide overuserevealed that the poor have a significantly lower probability of overusing. 13 Other variables thatcontributed to the determination of overuse were farm size, income and the proportion of WHO

12 The non-poor were more likely to misuse pesticides; significantly different at the 5% level of significance.

Non-poor (n=524)

No

90.1%

I don't

know5.3%

Yes

4.6%

Poor (n=79)

Yes

1.3%

I don'tknow

3.8%No

94.9%

0.00

0.20

0.40

0.60

0.80

1.00

1.20

Insecticides

***

Herbicides

***

Fungicides

***

Acaricides

***

Nematicides Bactericides Rodenticides

kilograms



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class II pesticides used in production. Overuse was also found to be more prevalent in theprovinces of An Giang and Cantho.

Table 4: Perceived risk of pesticides by poor/non-poor.

Perceived risk Poor Non-poor

High risk 30.4 21.0

Medium risk 25.3 26.3Small risk 27.8 31.1

No risk 13.9 20.4

Dont know 2.5 1.1

Total 100.0 100.0

Sample size (n=) 79 524

Increasing a farmers awareness of pesticide risk is an important first step in designing anyprogram on safer alternatives, however, do farmers think that the pesticides they are using poseany significant risks to their health and the environment? According to the studys results in Table4, only 42% of the poor and 52% of the non-poor think the pesticides they are using pose small orno risks. In addition, the low level of uncertainty (Dont know) leads us to believe that a high

percentage of farmers regard their pesticide use as hazardous, however, it may be the case thatthey are unaware of the exact health consequences.

III C) PESTICIDECONTROLMEASURESANDAVERTINGBEHAVIOR

As an alternative to pesticide use, other pest management methods are possible and appear tobe gaining traction in Vietnam. The main appeal to alternative methods is that the farmerdecreases his/her use of pesticides and it is therefore considered a more safer alternative.Examples of other methods include Integrated Pest Management (IPM: an ecologically-basedapproach to control of harmful insects and weeds 14), biological control (use of natural or modifiedorganisms, genes, or gene products to reduce the effects of pests and diseases), or organicmethods (farming that avoids the use of synthetic chemicals and genetically modified organisms(GMOs)).

Among the farmers sampled in the Mekong Delta, approximately 32% of the non-poor practicealternative pest control methods and 21% among the poor (Figure 4).15 The most popular controlmethod across both the poor and non-poor is Integrated Pest Management (IPM), thenmechanical-physical techniques (such as manual weeding) and biological control measures. Thelevel of adoption appears to be higher for the non-poor leading to a possible explanation that thenon-poor may have better access to information and training on alternative methods. This wasindeed verified when 54% of the non-poor (versus 37% for the poor) stated that they had receivedformal training on IPM methods. Thus if the policy goal is to train that segment of the populationthat is relative more unaware, one could either include more poor people in the program or havea program that targets them solely.

Figure 5: Prevalence of pest control measures by poor/non-poor.

13 In the (probit) modeling exercise overuse was defined as the dose amount over the label then summedacross all pesticides used. It was then coded as =1 for positive amounts, 0 otherwise.14

IPM uses better knowledge of local conditions to maintain yields while reducing chemical inputs. IPM

relies on natural parasites and predators to control pest populations whenever possible. Farmers in manydeveloping countries have used IPM to cut chemical pesticide use by limiting applications to areas wherenatural controls are insufficient.15 This difference is statistically significant at the 1% level of significance.

Poor (n=79)

Rotation of

crop

0.4%

Organic

production

0.4%

Other

0.4%

Biological

control

3.4%

Do not use

pest control

78.9%

Mechanical-

physical

techniques

7.6%

IPM

8.9%

Non-poor (n=524)

Rotation of

crop

0.1%

Organic

production

0.4%

Other

2.0%

Biological

control

4.7%Do not use

pest control

68.2%

Mechanical-

physical

techniques

8.8%

IPM

15.8%


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The education of farmers on safer alternatives is one piece of a two-part initiative on raisingawareness and improving farmer productivity. The second part is to increase education on thesafe handling and application of pesticides. As was earlier discussed, even simple knowledge of

the relative toxicity may induce the farmer to take remedial or more protective actions in the short-term. From our survey evidence, in Figure 6 we see that only about 29% of the poor and 34% ofthe non-poor had any formal training on pesticide safety. This difference was not significantlydifferent leading us to believe that the poor have the same access to information as the non-poor.

Figure 6: Prevalence of basic training on safe handlingand application of pesticides by poor/non-poor.

The potential suppliers of pesticide information may enter at different stages of the pesticide usedecision. As mentioned above, one stage may be ex-post, or after the farmer has chosen what touse and is now learning more about the pesticide they were using in the past. Another is at thepurchasing stage or retailer level. When purchasing pesticides, farmers may also have theopportunity to learn more about the pesticide through pamphlets, brochures and other media.

This information may influence the pesticide decision and would be particularly helpful to thefarmer in terms of understanding what is needed to adequately prepare for the application (e.g.how much to apply, what the pesticide can be used for or on, what protective measures arenecessary for avoiding exposure, etc).

Among the sample of farmers in this study, only 42% of the non-poor reported receiving safetyinformation and procedures on pesticide use versus only 39% for poor farmers. Of the farmerswho received information, the main source of the information was from the public media, pesticidecompanies and agricultural officials (Table 5). The significant role of the public media for the poor

Poor (n=79)

Yes

29.1%

No

70.9%

Non-poor (n=524)

No

65.8%

Yes

34.2%


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by poor/non-poor (%).

Shoes Hat Glasses Mask Shirt Trousers Gloves

Reasons PoorNon-poor

PoorNon-poor

PoorNon-poor

PoorNon-poor

PoorNon-poor

PoorNon-poor

PoorNon-poor

Not available 19.3 16.5 51.2 40.7 32.9 25.2 16.2 16.2 0.0 5.0 0.0 0.0 19.2 17.8

Uncomfortable 16.9 23.8 31.7 39.6 34.2 41.4 54.1 52.5 100.0 45.0 80.0 68.0 41.1 45.4

Inappropriate 48.2 42.6 2.4 7.0 12.3 12.7 10.8 10.8 0.0 20.0 0.0 4.0 13.7 13.0Unnecessary 12.0 10.1 12.2 8.5 16.4 16.4 13.5 12.3 0.0 20.0 0.0 8.0 19.2 19.1

Other 3.6 6.9 2.4 4.1 4.1 4.2 5.4 8.3 0.0 10.0 20.0 20.0 6.8 4.7

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1 00.0 100.0 100.0

Sample size(n=)

79 524 79 524 79 524 79 524 79 524 79 524 79 524

III D) HEALTH

The health consequences of pesticide use were recorded during the survey. Two types of datawere collected, farmer self-reported and medical test data. Self-reported data is often collected inthe absence of full medical test data, as test data may be either cost or time prohibitive. In this

study we opted to collect both self-reported and medical test data to facilitate a comparisonbetween the two and to test the reliability of farmer self reporting. It should be noted that themedical survey covered only 482 out of the 603 farmers from the socio-economic survey. Theremainder of these were unreachable at the time of the medical survey.

Among the various self-reported health impairments after using pesticides, a high percentage ofboth the poor and non-poor experienced acute (or short-term) health effects such as skinirritations, headaches, dizziness, eye irritations and shortness of breath (Figure 8). Upon askingthe farmers whether they believed that these symptoms were related to pesticide use, 81% ofpoor and 82% of non-poor farmers believed this to be true.

Figure 8: Self-reported health impairments after using pesticides (%).

To further confirm the evidence of the extent of pesticide-related health problems, a team ofmedical doctors17 were deployed to screen and test farmers for pesticide exposure. An initialscreening was conducted using several key indicators that are important in the identification of

17 Medical doctors from the Centre of Occupational and Environmental Health (COEH) of the VietnamAssociation of Occupational Health (VINOH), Hanoi, Vietnam.

0

10

20

30

40

50

60

70

Skin

irritation

Headache Dizziness Eye

irritation

Other

problems

Shortness of

breath

Fever Vomiting Convulsions Diarrhea

Percentage



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potential pesticide exposure prevalence of skin diseases, blood pressure, respiratory ailmentsand heart disease. Tests revealed a fairly high prevalence of skin diseases among all farmers(28-33%), with the poor showing a higher symptomatic rate for each of skin disease (otherdermatose), heart disease, respiratory ailments and blood pressure (Table 7).

Table 7: Medical examination results for common problems relating to pesticide use bypoor/non-poor (%).

SkinPoor

Non-poor

BloodPoor

Non-poor

RespiratoryPoor

Non-poor

HeartPoor

Non-poor

Normal 58.6 60.2 Normal 80.0 89.3 Normal 95.7 98.3 Normal 98.6 99.3

Irritant 2.9 4.6 Low 5.7 2.4 Pneumonia 0.0 0.2 Positive 1.4 0.7

Allergic 5.7 6.8 High 14.3 8.3 Bronchitis 4.3 1.5

Otherdermatose

32.9 28.4

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Sample size 70 412 70 412 70 412 70 412

Figure 9: Medical skin tests for the detection and reactivityof commonly used pesticides, by poor/non-poor (%).Skin test: Poor (n=60)

Positive

reaction

38.3%

Normal

61.7%

Skin test: Non-poor (n=153)

Normal

68.6%

Positive

reaction

31.4%


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Building upon the initial screening exam, detailed patch-skin tests18 were conducted on thesample of farmers to gauge dermal (skin) exposure to pesticides. Results show thatapproximately 38% of the poor and 31% of the non-poor registered a positive reaction (Figure 10:top).19 A second stage of skin testing resumed with three of the most commonly used pesticidesin the region, Karate (WHO category II), Basudin (WHO II) and Padan (WHO II).20 Test results inthe bottom of Figure 9 show that on average 15-25% of farmers experienced a strong toextreme reaction to these pesticides implying that exposure, from a dermal perspective, issignificant among those farmers tested. Only small differences in positive reaction wereobserved between the poor and non-poor, with the largest being for Basudin (organophosphate)at 4%.

18 Selection criteria included the symptoms of contact dermatitis, such as skin itch, prurigo, skin irritation,

and allergy. The purpose of the test was to diagnose farmers suffering from some form of pesticide contactdermatitis (irritant contact dermatitis and allergic contact dermatitis).19 A statistical analysis of blood test results revealed that there was no significant difference in meanpesticide poisoning for poor and non-poor. A further regression analysis of blood test results revealed thatthe key determinants of poisoning werepesticide amount, theproportion of WHO class Ia and Ib pesticidesused in production and the number of protection measures taken. The prevalence of blood poisoning wasalso found to be higher in the provinces of Cantho and Tien Giang.20 Karate 2,5 EC: Pyrethroid, Basudin 50 EC: Organophosphate and Padan 50 SP: Carbamate.

8 1017 13 13

16

7 7 8 8 10 6

85 84 77 787975

0

10

20

30

40

50

60

70

80

90

100

Poor

(n=60)

Non-poor

(n=153)

Poor

(n=60)

Non-poor

(n=153)

Poor

(n=60)

Non-poor

(n=153)

Karate Basudin Padan

Percentage

Weak reaction Strong reaction Extreme reaction


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Figure 10: Medical blood tests for the detection of acute and chronic pesticide poisoning,by poor/non-poor (%).

Severity of poisoning Poor Non-poor

Acute poisoning 40.0 42.9

Chronic poisoning 60.0 57.1

Total 100.0 100.0

Sample size 25 42

A third stage of pesticide exposure testing resumed with detailed blood tests.21 Results indicate(Figure 10: top) that the poor experience a higher prevalence rate of blood poisoning than non-poor (42% versus 33%). Among those who tested positive for blood poisoning (25 poor, 42 non-poor ), fifteen or 60% of the poisoned poor were found to be chronic cases, and 24 or 57% ofnon-poor (Figure 10: bottom table).

IV. CONCLUSIONAND DISCUSSION

Pesticide use has been on the rise in Vietnam, notably over the past decade with a near doublingof consumption from 1990-1998. Field evidence has suggested that farmers are also misusingand overusing pesticides in order to maintain crop yields and production. As a consequence ofthis growing dependence and hap-hazard use of pesticides, the prevalence of health impairmentsand environmental damage are mounting.

The purpose of this component of the Poverty-Environment Nexus study is to answer twoquestions relating to pesticide use in Vietnam, 1) Are the poor using more, toxic pesticides?, and2) Is pesticide use, and its attended health consequences, impacting the poor to a greater extentthan the non-poor? A World Bank survey of 603 farmers was conducted in the Mekong Delta,Vietnam, an area known for extremely intensive agriculture. The survey comprised two majorsections, one to gather information on crop production and related pesticide use by farmers, andone on the health and medical condition of the farmer.

In regards to the first major question, survey results indicate that although the poor are currentlyusing smaller amounts of pesticides (as well as on a per hectare basis), they are using relativelymore toxic pesticides. Several toxicity indicators were constructed to measure a pesticidesdegree of relative toxicity. By weighting a pesticides active ingredient by its degree of lethality (or

21 The test was a cholinesterase enzyme technique measuring active cholinesterase enzymes in erythrocyte

and plasma using the Test-Mate-Kit (EQMR-USA), with 0.03ml of blood from the fingertip. The purpose ofthis test was to aid in the diagnosis and detection of persons suffering from pesticide poisoning (organic-phosphates and carbamates).

Blood tes t: Poor (n=59)

Normal

57.6%

Poisoning

42.4%

Blood tes t: Non-poor (n=129)

Poisoning

32.6%

Normal

67.4%


16/18

by the LD50 value) and categorizing this measure according to the WHO risk classification system,the poor are using a greater percentage of WHO Ia & Ib pesticides. Analogously, by classifyingpesticide use by its chemical class, it was found that the non-poor are using a greater amount ofcarbamates, organophosphates, and pyrethroids.

In regards to the second question, farmer self-reported and medical test data were compiled andcompared. A large proportion (40-60%) of poor and non-poor farmers reported episodes of skinirritation, headaches, dizziness, eye irritation and shortness of breath after using pesticides.Upon closer examination by medical doctors, although few were suffering from heart disease,respiratory ailments or large abnormalities in blood pressure, approximately 33% of the poor and28% of the non-poor experience some type of skin disease (under the classification otherdermatose). Patch-skin tests for external pesticide exposure revealed that approximately 38% ofthe poor and 31% of the non-poor farmers reacted positively to the presence of pesticides. Bloodtests for internal pesticide poisoning showed that the poor (25 out of 59 or 42%) had a slightlyhigher prevalence rate than the non-poor (24 out of 153 or 32%), however this difference was notstatistically significant.

V. REFERENCES

Comprehensive Poverty Reduction and Growth Strategy (CPRGS), 2002. Document No.2685NPCP-QHQT, Hanoi, Vietnam.

Chung, D. K. and K. T. Dung. 2002. Pest Management in Rice Production in Vietnam: A Socio-economic Assessment. Hanoi: Nha Xuat Ban Nong Nghiep.

Dung, N. H. and T. T. T. Dung, 1999. Economic and Health Consequences of Pesticide Use inPaddy Production in the Mekong Delta, Vietnam. EEPSEA Research Report No.1, pp. 1-39.Available at: http://www.eepsea.org/en/ev-8427-201-1-DO_TOPIC.html.

FAO, 2001. Farmer Self-Surveillance of Pesticide Poisoning Episodes: Report on One Month

Pilot: August 15-Sept 15, 2000. FAO Programme for Community IPM in Asia, Field Document.

FAO, 2004. FAO-STAT. Statistics downloaded for Vietnam. Available at:http://apps.fao.org/default.jsp.

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PEN Report Pesticide Use in Vietnam Mar2005

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