Industrial Effluent And Health Status Of Noyyal Basin Biology Essay

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Pollution in Great lakes is a major threat to human welfare as it degrades the environment affecting the water we use and the air we breathe. Industrial and household waste water contains low level of dissolved oxygen due to heavy biological oxygen demand and chemical oxygen demand placed by industrial and household waste materials discharged in water system. Discharge of chemicals, pesticides , persistent organic pollutants, heavy metals via industrial effluents is a great threat to human health and ecosystem.

Polluted water affects human productivity, land productivity, crop production due to contaminated irrigation water, animal husbandry, fishery, biological effects like ill health, change in biodiversity or effects on health from harmful chemicals. Most of the water- borne diseases are Skin allergy, defective vision, respiratory infections, general allergy, gastritis, ulcers, fever, tooth corrosion, joint pains, loss of appetite, abdominal pain, diarrhea.

Issue : Mortality among frequent consumers of great lakes sport fish.

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As per the health professionals commercial and sport-caught fish intake in meal lowers the risk of heart diseases as they are healthy sources of dietary protein, omega-3 fatty acids and other micronutrients. Bioaccumulative chemicals found in Great lake fish such as methyl mercury, PCBs, dieldrin,DDT have been linked with adverse effects on human health like change in cognitive abilities and endocrine function to certain types of cancers .Levels of these chemicals are contaminating the sediments of great lakes and can be detected in older, predatory fish .During critical periods of fetal brain development, MeHg can interfere with the growth and migration of the neurons. Maternal exposure during these periods can cause permanent brain damage with life long effects on intelligence and coordination (Bakir et al.,1973; Harada, 1978;NRC,2000).Adult exposure can cause clinical symptoms like paresthesia, blurred vision, mental confusion, hearing impairment, cardiovascular diseases ( due to elevated mercury levels above federal guideline of 1ppm in hair or toenails).

A cohort of 4000 residents of Great lake basin was used to evaluate the impacts of local sport fish consumption on cause specific mortality rate. Study population was comprised of 1994-1995 data of 2527 Great lake Charter boat captains, 179 wisconsin anglers who were the frequent consumers and 1141 referents who did not ate Great lake sport fish. Referents were recruited by a random digital dial telephone survey. For ascertainment of mortality data the National centre for health statistics provided death records from the National death index that matched the cohort identifiers. Records were matched using name, birth date, last address, sex and race. Matches provided 342 deaths of coherent members. Primary exposure measure used for analysis were the annual estimates of total fish consumption and number of meals that were sport-caught Great Lakes fish meals. Fish consumption was defined as number of all types of fish meals consumed during 12 months prior to telephonic interview. captions were asked to provide species- specific Great lake fish consumption estimates, which were summed. Sum was used as annual intake estimate. Fish intake rates were categorized as low (0-1 meals/month), moderate(>1 meal/month and <1 meal/week), or high (> or = to one meal/week). Race was classified as white, black and other. Age in 1995 was analyzed as continuous variable. Body mass . index was calculated from self- reported weight and height measurements. Limited smoking and alcohol data were available along with mean days of alcohol consumption per month.

The leading cause of death were cancer which accounted for (134) and Cardio Vascular diseases (109).All cause and CVD mortality rates were lower among cohort members relative to general population aged >/35 years in Midwestern US. A higher percentage of cancer deaths was observed among captains than referents. (43.2% versus 34.1%). Cancer rates in cohorts were similar to those in the general population. Age- adjusted cancer death rates were slightly higher among the captains than among referents (394.8 versus 378.6), while the referent group had higher rates of cardiovascular and respiratory system disease deaths than captains (465.7 and 96.6 versus 397.4 and 89.5). >/1 fish meal /week was protective against all cause, CVD and CHD mortality in referents whereas fish intake was not protective among captains. 1 year increase in age was associated with 10% increase in mortality. 6 of 8 deaths occurred in captions due to pancreatic cancer, 5 of 6 due to brain cancer, 5 of 6 due to female breast, ovary and uterus and 2 of 2 due to soft tissue sarcoma. Multivariate analysis of death arte confirmed a dose- related protective effect of fish intake against all cause and cardiovascular disease mortality, including coronary heart disease among referent group but was not observed among the consumers of Great lakes sport fish. Overall death rate is lower in cohort compared to general Midwest population due to difference in age distribution( 6% people over 70 years compared to 19%).Thus this raise concerns regarding the effect of persistent environment contaminants that continue to be detected in fish from Great lake basin. It should be continuously monitored to understand the complex interaction that exist between nutrients and contaminants found in fish harvested from Great lakes.

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Table 1. Selected baseline characteristics (1995) of the Great Lakes cohorta by fish intake for captains and referents.

Baseline characteristics, 1995

Captains (N=2274)

Referents (N=1449)

Fish meal consumption

Fish meal consumption

0-1/month (N=359)

>1/month to<1/week (N=849)

1/week (N=1066)

p-valueb

0-1/month (N=740)

>1/month to<1/week (N=401)

1/week (N=308)

Age in years - Mean (SD)

48.2 (9.4)

47.6 (10.2)

49.2 (10.5)

0.005

45.8 (13.2)

45.3 (13.2)

49.1 (13.6)

Sex (%)

 Male

73.8

73.0

77.4

0.072

68.0

64.3

74.7

 Female

26.2

27.0

22.6

32.0

35.7

25.3

Race (%)

 White

98.9

99.2

99.2

0.864

94.7

97.0

95.1

 Black

0.5

0.1

0.3

1.5

1.0

1.0

 Other

0.3

0.5

0.3

1.8

1.3

1.3

 Missing

0.3

0.2

0.2

2.0

0.7

2.6

Highest education attained (%)

 4-year college degree

20.1

25.3

24.0

0.001

23.5

35.2

36.0

 Some college

25.3

30.2

32.8

23.1

20.2

23.4

 High school degree

46.5

41.0

39.6

42.6

39.4

33.8

 Some high school

8.1

3.4

3.5

9.9

4.7

5.2

 Missing

0

0.1

0.1

0.9

0.5

1.6

Annual income in dollars (%)

 50,000

35.7

35.4

35.7

0.766

25.3

33.7

32.5

 49,999-35,000

28.1

30.4

27.7

25.0

25.7

22.7

 34,999-25,000

16.4

16.0

15.7

19.2

17.0

19.8

 24,999

15.0

12.2

14.5

26.9

17.4

18.8

 Missing

4.7

6.0

6.4

3.7

6.2

16.2

Body mass index (%)

 <25

29.8

32.0

25.6

0.034

40.7

37.7

38.0

 25-29

47.9

46.3

47.6

43.8

45.4

42.5

 30

21.2

20.9

26.0

13.9

15.7

17.5

 Missing

1.1

0.8

0.8

1.6

1.2

2.0

Smoking prevalencec (%)

21.2

20.1

22.8

0.520

23.1

14.4

18.0

Days per month consuming alcohold-Mean (SD)

7.4 (9.2)

8.9 (9.9)

9.5 (10.1)

0.074

5.8 (9.1)

5.1 (7.9)

8.7 (9.8)

Years consuming GLSFe-mean (SD)

23.2 (12.8)

24.6 (12.8)

27.3 (13.5)

<0.001

-

-

-

PCB levelf (μg/l)-mean (SD)

3.6 (3.2)

4.7 (4.9)

6.2 (5.8)

<0.001

2.9 (6.7)

1.7 (1.5)

2.4 (2.5)

a 124 cohort members were unable to be classified with respect to fish consumption and are excluded from table.

b χ2 Test was used to test for difference in sex, race, education, income, body mass index, and smoking prevalence by fish intake within captains and referents and between. One-way analysis of variance was used to test for difference in mean age, days of alcohol consumption per month, years of consumption of Great Lakes sport-caught fish, and PCB level by fish intake.

c Not ascertained at baseline, but correspond to 2254 persons who provided smoking data in a 2003 follow-up survey.

d Not ascertained at baseline, but correspond to 1580 persons who provided alcohol consumption data in a 2003 follow-up survey.

e Calculation limited to captains.

f PCB levels limited to 610 persons who provided blood for analysis.

Table 2. Major causes of death in Great Lakes cohort by gender for captains and referentsa.

Cause (ICD-9 codes; ICD-10 codes)

Males

Females

Captains (N=1710)

Referents (N=1008)

Captains (N=565)

Cancer (140-208;C00-C97)

70

39

13

 Digestive organs (150-159;C15-C26)

18

9

1

 Pancreas (157;C25)

5

2

1

 Respiratory (161-162;C32-C34)

22

15

3

 Skin (172-173;C43-C44)

2

2

1

 Female breast, uterus, ovary

-

-

5

 Male breast

1

0

-

 Male genital organs (185-187;C60-C63)

3

2

-

 Urinary tract (188-189;C64-C68)

7

0

0

 Brain (191;C71)

4

1

1

 Lymphoid/hematopoietic (200-208;C81-C96)

8

8

1

Endocrine, nutritional, and metabolic diseases (240-279;E00-E88)

9

6

0

 Diabetes (250;E10-E14)

6

5

0

Cardiovascular disease (390-459;I00-I99)

55

45

3

 Ischemic heart diseases (410-414;I20-I25)

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30

21

1

 Other heart disease (420-429;I30-I51)

3

8

0

 Cerebrovascular diseases (430-438;I60-I69)

11

9

0

 Diseases of arteries, arterioles, capillaries (440-448;I70-I78)

2

2

0

Respiratory system diseases (460-519;J00-J98)

13

9

2

 Influenza and pneumonia (480-487;J10-J18)

4

1

1

 Chronic lower respiratory diseases (490-494, 496;J40-J47)

6

6

1

Digestive system diseases (520-579;K00-K92)

3

5

1

External causes of mortality (800-999;V01-Y89)

9

5

2

 Unintentional injuries (E800-E949;V01-X59)

4

5

2

Other causes

11

13

3

All causes

171

122

24

a 90 cohort members and 9 deaths were unable to be classified with respect to Great Lakes sport fish consumption and are excluded from table.

Table 3. Age-adjusted rates for the top 5 causes of death among Midwestern US adults, captains, and referents.

Top 5 causes of death

ICD-10 codes

Age-adjusted death rate per 100,000 person-years

Midwest USa

Captains

Cardiovascular disease

I00-I99

606.1

397.4

Neoplasms

C00-D48

389.8

394.8

Respiratory system disease

J00-J98

156.0

89.5

Nervous system disease

G00-G98

73.1

51.0

External causes

V01-Y89

71.8

52.9

All causes

1572.0

1103.7

a Leading causes of death for Midwest residents aged 35 years, 1999-2006, CDC WONDER compressed mortality data accessed at wonder.cdc.gov on July 8, 2008.

Table 4. Adjusted hazard ratiosa for all-cause mortality associated with fish intake, 1995-2006b.

Captains (N=2123)

Referents (N=1367)

# Events

HR

95% CI

# Events

HR

Fish meals intake

0-1/month

24

1.00

Reference

70

1.00

>1/month to<1/week

66

1.14

0.72-1.83

29

0.76

1/week

87

1.00

0.63-1.58

29

0.60*

Abbreviations: CI, confidence interval; HR, hazard ratio.

*Significant at p<0.05.

a Models were adjusted for sex, age, body mass index, and income at study baseline.

b Exclusions to the multivariate analysis include 233 persons, whose data were missing for one or more of the analysis variables.

Table 5. Adjusted hazard ratiosa for cardiovascular disease (CVD) and coronary heart disease (CHD) mortality associated with fish intake, 1995-2006b.

Cardiovascular disease

Captains (N=2123)

Referents (N=1367)

# Events

HR

95% CI

# Events

HR

Fish meals intake

0-1/month

7

1.00

Reference

26

1.00

>1/month to <1/week

17

0.94

0.39-2.29

8

0.56

1/week

27

0.97

0.42-2.26

10

0.45*

Coronary heart disease

Captains (N=1609)

Referents (N=940)

# Events

HR

95% CI

# Events

HR

Fish meals intake

0-1/month

3

1.00

Reference

16

1.00

>1/month to <1/week

11

1.48

0.41-5.32

6

0.74

1/week

20

1.81

0.53-6.16

4

0.31*

Abbreviations: CI, confidence interval; HR, hazard ratio.

*Significant at p<0.05.

a Models were adjusted for sex, age, body mass index, and income at study baseline.

b Exclusions to the multivariate analysis include 233 persons, whose data were missing for one or more of the analysis variables. In addition, CHD analyses were limited to men, since only one female died from CHD in each captain/referent group.

Table 6. Adjusted hazard ratiosa for cancer mortality associated with fish intake, 1995-2006b.

Captains (N=2123)

Referents (N=1367)

# Events

HR

95% CI

# Events

HR

Fish meals intake

0-1/month

11

1.00