ERF of omega-3 fatty acids

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Question

What is the exposure-response function (ERF) of omega-3 fatty acids on several health end points?

Answer

+ Show code- Hide code library(OpasnetUtils) objects.latest("Op_en5830", code_name = "initiate") # [[ERF of omega-3 fatty acids]] ovariables ERF, threshold. oprint(summary(EvalOutput(ERF_omega3)))

Rationale

⇤--#: . This article should be checked:

• Is fish oil good for you? Depends on your DNA. Elizabeth Pennisi. Science 17 September 2015 [4] --Jouni (talk) 10:35, 7 October 2015 (UTC) (type: truth; paradigms: science: attack)

⇤--#: . Dose-response_function_of_cardiovascular_effects_of_omega-3_fatty_acids this should be included --Arja (talk) 07:10, 21 September 2016 (UTC) (type: truth; paradigms: science: attack)

Data

ERF of omega-3 fatty acids(-)

Obs	Exposure agent	Response	Sex	Exposure	Exposure unit	ER function	Scaling	Threshold	ERF	Description
1	DHA	Change in child's IQ points		Maternal intake through placenta	mg /kg bw /day	ERS	BW	0	0.07 +- 0.01	Cohen et al. 2005; Gradowska 2013; Standard deviation
2	DHA	Change in child's IQ points		Maternal intake through placenta	mg /day	ERS	None	0	0.0013 (0.0008 - 0.0018)	Cohen et al. 2005; also according to Zeilmaker 2013
3	Omega3	Coronary heart disease mortality		Ingested intake of EPA+DHA from fish	mg /day	RR	None	0	0.9980 +- 0.000396	Mozaffarian and Rimm 2006; Gradowska 2013 slope = -0.002, SD = exp(-0.002)-exp(-0.002+3.97E-4)
4	Omega3	CHD arrythmia mortality		Ingested intake of EPA+DHA from fish	mg /day	Relative Hill	None	200	-0.3	Mozaffarian and Rimm 2006
5	Omega3	CHD2 mortality		Ingested intake of EPA+DHA from fish	mg /day	Relative Hill	None	47	-0.17 (-0.25 - -0.088)	Cohen et al 2005. "antiarrhythmic effect". No-exposure is <1 serving/mo, therefore ED50 = two servings per month = 1400 mg/mo = 47 mg/d
6	Omega3	CHD2 mortality		Ingested intake of EPA+DHA from fish	mg /day	RR	None	0	0.99951 (0.99934 - 0.99989)	Cohen et al 2005 "antiatherosclerotic effect". 1-0.039*0.01
7	Omega3	Stroke mortality		Ingested intake of EPA+DHA from fish	mg /day	Relative Hill	None	47	-0.12 (-0.25 - 0.01)	Cohen et al. 2005
8	Omega3	Stroke mortality		Ingested intake of EPA+DHA from fish	mg /day	RR	None	0	0.9998 (0.99934 - 1.00027)	1-0.02*0.01, Cohen et al 2005: −2.0% 95% CI: +2.7% to −6.6%
9	Fish	Subclinical brain infarct (one or more) prevalence		Ingested intake of tuna/other fish	≥3 times/week vs. <1/month	RR	None	0	0.74 (0.54 - 1.01)	Virtanen et al. 2008; 95% CI
10	Fish	Any prevalent subclinical brain infarct prevalence		Ingested intake of tuna/other fish	Each one serving per week	RR	None	0	0.93 (0.88 - 0.994)	Virtanen et al. 2008; 95% CI
11	Fish	Subclinical brain infarct (one or more)incidence		ngested intake of tuna/other fish	≥3 times/week vs. <1/month	RR	None	0	0.56 (0.30 - 1.07)	Virtanen et al. 2008; 95% CI
12	Fish	Any incident subclinical brain infarct incidence		Ingested intake of tuna/other fish	Each one serving per week	RR	None	0	0.89 (0.78 - 0.993)	Virtanen et al. 2008; 95% CI
13	Fish	Status of cerebral white matter grade score		Ingested intake of tuna/other fish	Each one serving per week	ERS	None	0	0.038	Virtanen et al. 2008; 95% CI

ERF publications

ERF data as described in original articles

Exposure agent	Trait	Response metric	Exposure route	Exposure metric	Exposure unit	ERF parameter	Threshold	ERF	Description
DHA	Child´s IQ	Change in IQ points	Placenta	Maternal intake	mg/kg bw/day	ERS	0	0.07(±0.01)	Cohen et al. 2005; Gradowska 2013
Omega3	CHD	Δlog(CHD mortality rate)	Ingestion	Intake from fish	mg/day EPA+DHA	ERS	0	-0.002 (±3.97E-4)	Mozaffarian and Rimm 2006; Gradowska 2013
DHA and EPA	Stroke	Incidence	Ingestion	Dietary intake of EPA+DHA	520 mg /day vs. 148 mg /day	RR	0	0.72 (0.54-0.96)	Multivariable- and PCB-adjusted RR (95% CI) Bergkvist et al. 2014
Fish	Subclinical brain infarct (one or more)	Prevalence	Ingestion	Intake of tuna/other fish	=3 times/week vs. <1/month	RR	0	0.74(0.54-1.01)	Virtanen et al. 2008
Fish	Any prevalent subclinical brain infarct	Prevalence	Ingestion	Intake of tuna/other fish	Each one serving per week	Decrease in RR %	0	7(0.6-12)	Virtanen et al. 2008
Fish	Subclinical brain infarct (one or more)	Incidence	Ingestion	Intake of tuna/other fish	=3 times/week vs. <1/month	RR	0	0.56(0.30-1.07)	Virtanen et al. 2008
Fish	Any incident subclinical brain infarct	Incidence	Ingestion	Intake of tuna/other fish	Each one serving per week	Decrease in RR %	0	11(0.7-22)	Virtanen et al. 2008
Fish	Status of cerebral white matter	Grade score	Ingestion	Intake of tuna/other fish	Each one serving per week	Increase in grade score %	0	3.8	Virtanen et al. 2008
Fish	Cerebrovascular disease	Incidence	Ingestion	Intake of fish	2-4 versus ≤1 servings a week	RR	0	0.94 (0.90-0.98)	95% CI, Meta-analysis based on 18 and eight studies Chowdhury et al,. 2015
Fish	Cerebrovascular disease	Incidence	Ingestion	Intake of fish	≥5 versus ≤1 servings a week	RR	0	0.88 (0.81-0.96)	95% CI, Meta-analysis based on 18 and eight studies Chowdhury et al,. 2015
Fish	Cerebrovascular disease	Incidence	Ingestion	Intake of fish	Increment of two servings per week	Reduced risk	0	0.04 (0.01-0.07)	95% CI, Meta-analysis based on 18 and eight studies Chowdhury et al,. 2015
Fish	thrombotic infarction	Incidence	Ingestion	Intake of fish	2 or more times per week vs. <1 serving per month	RR	0	0.49 (0.26-0.93)	95% CI, Iso et al. 2001

Exposure-response of fish oil intake for MI risk in adults is indexed by variable age. It applies to age categories > 18 years.

The study by Cohen et al. 2005 estimates that increasing maternal docosahexaenoic acid (DHA) intake by 100 mg/day increases child's IQ by 0.13 points D↷. This value represents central estimate while the upper and lower bound for this ERF is 0.08 and 0.18. Triangular distribution is used.

In a recent study, 3660 over 65-year-old individuals were monitored for five years, and the change in small brain infarctions was observed by magnetic resonance imageing. The infaction risk was 25 % lower in those who ate at least three portions of omega-3-rich fish meals per week, and 13 % lower in those who ate one meal per week.

Fernandez-Jarne et al. examined the relationship between intake of fish and n-3 PUFA and the risk of first acute myocardial infarction (AMI) in a low risk population from Navarre (Spain). They found that the n-3 PUFA intake has a protective effect on AMI. The adjusted odds ratio (OR) for the second and third tertile of n-3 PUFA intake were 0.44 (95% Cl, 0.21-0.91) and 0.47 (95% Cl, 0.22-1.00), respectively. The trend test was not statistically significant. D↷

Mozaffarian and Rimm estimated that at intakes between 0 and 250 mg/d, the relative risk of coronary heart disease (CHD) death is lower by 14.6% (95% CI: 8% to 21%) per each 100 mg/d of EPA and DHA intake and that at higher intakes ( > 250 mg/d) the risk reduction is 0.0% (95% CI: -0.9% to 0.8%) per each 100 mg/d.

The ERF of omega-3 fatty acids (DHA+EPA) intake from fish (in unit of mg/kg bw-day) on the CHD mortality is estimated based on information provided in . First, the central estimate and the 95% CI for the change (in this case decrease) in natural logarithm of relative risk (RR) of CHD mortality per unit change in omega-3 fatty acids intake (in unit of mg/day) in both intake intervals were derived. In general, the relationship between the percent change in RR (%RR) associated with c-unit increase in omega-3 fatty acids intake and the incremental change in lnRR (beta) per unit change in omega-3 fatty acids intake is beta = (1/c)*ln((%RR/100)+1). Normal distribution was chosen to describe the uncertainty in the parameter of the log-linear model for RR in each intake interval. For intake of EPA+DHA between 0 and 250 mg/day the mean and the standard deviation of parameter distribution are -0.0016 and 0.0004, for higher intakes 0 and 0.0005. Then, the distribution of ERF of omega-3 fatty acids intake from fish in units of mg/kg bw-day was obtained by multiplying ERFs of omega-3 fatty acids intake measured in mg/day by the body weight of adult.

In cohort studies comparing categories of fish intake the pooled relative risk for cerebrovascular disease was demonstrated based ob 26 prospective cohort studies and 12 randomised controlled trials with aggregate data on 794 000 non-overlapping people and 34 817 cerebrovascular outcomes by a review by Chowdhury et al. 2015

In a study by Iso et al. 2001 a significant inverse associations between fish intake and age- and smoking-adjusted risk of total stroke, ischemic stroke, and thrombotic infarction, specifically lacunar infarction was found. After further adjustment for other cardiovascular and selected dietary variables, the inverse remained significant for thrombotic infarction and lacunar infarction, with a reduced risk of these stroke subtypes among women who ate fish 2 or more times per week. The multivariate RRs were 0.49 (95% CI, 0.26-0.93; P = .03), and 0.28 (95% CI, 0.12-0.67; P = .004), respectively. We found no excess risk of hemorrhagic stroke, either intraparenchymal or subarachnoid hemorrhage, among women who ate fish frequently.

Unit

lnRR/ 1 (mg/kg bw-day) change in EPA+DHA intake from fish

Beneris distributions

For intakes of EPA+DHA from fish between 0 and 250 mg/day: N(-0.0016,0.0004)*BW

For intakes of EPA+DHA from fish higher than 250 mg/day: N(0,0.0005)*BW

Summary of dose–response relationships

Health effect	Relationship	Central estimate	Uncertainty
Fish consumption and CHD mortality	ΔRR for some fish consumption vs no fish consumption (<1 serving/month)	−17%	95% CI a: −8.8% to −25%
	ΔRR per additional serving/week	−3.9%	95% CI a: −1.1% to −6.6%
Fish consumption and stroke incidence	ΔRR for some fish consumption vs no fish consumption (<1 serving/month)	−12%	95% CI a: +1.0% to −25%
	ΔRR per additional serving/week	−2.0%	95% CI a: +2.7% to −6.6%
MeHg exposure and cognitive development	ΔIQ per μg/g total Hg in maternal hair	−0.7 pts	Bounds: 0 to 1.5 pts
DHA intake and cognitive development	ΔIQ per g/day maternal intake of DHA	1.3 pts	Bounds: 0.8 to 1.8 pts

^a 95% CI is based on the distribution for this coefficient calculated from the regression analysis used to develop the dose–response relationship for CHD or stroke. CHD, coronary heart disease; CI, confidence interval; DHA, docosahexaenoic acid; MeHg, methyl mercury; pts, points; RR, relative risk. Serving size was 100 g.

Here we need to convert the serving size to omega-3 intake. It depends on the average omega-3 content in the diets of the patients in the studies, and it is not known to us. Therefore, we may assume that it is higher than in lean fish (0 - 0.5 %) and lower than in fatty fish (1-2 %), i.e. say 0.7 % or 700 mg per serving. Therefore, the published RR changes (per servings/week) must be multiplied by 1 per (servings * 700 mg/serving / (week * 7 d/week) = 0.01 * RR changes per mg/d. CHD2 is used as the trait to prevent double counting with the other ERFs based on Mozaffarian and Rimm.

In addition, Cohen concluded that the ERFs for CHD and stroke are non-linear with a larger reduction in risk between non-consumers and some-consumers (the limit defined as 1 serving per month). In addition, a linear incremental benefit was estimated for intakes more than 1 serving per week. This results in two independent ERFs where the low-dose "antiarrhythmic" effect follows Relative Hill function and the high-dose "antiatherosclerotic" effect follows RR function. Cohen assumed a negative correlation between these, but this is not easy to implement with the current HIA ovariables and therefore we ignore the correlation; this results in an increase of the estimated uncertainty in the model.

In a recent large cohort study by Engeset et al. (2015) no associations were seen for consumption of total fish, lean, or fatty fish and either total mortality or cause-specific mortality among men; broadly similar results were obtained for women. The statistical significant associations found in the non-calibrated analyses disappeared in the calibrated analyses and bootstrap analyses.

Calculations

+ Show code- Hide code library(OpasnetUtils) d <- opbase.data("Op_en5830") d$Obs <- NULL colnames(d) <- gsub(" ", "_", colnames(d)) d$Result <- ifelse(d$Result == "", "0", as.character(d$Result)) ERF_omega3 <- Ovariable("ERF_omega3", data = d[d$Observation == "ERF", colnames(d) != "Observation"]) threshold_omega3 <- Ovariable("Threshold_omega3", data = d[d$Observation == "Threshold", colnames(d) != "Observation"]) objects.store(ERF_omega3, threshold_omega3) cat("Ovariables ERF, threshold stored.\n")

See also

• ERF of methyl mercury
• A press release from the University of Kuopio (in Finnish)
• Reviews by Henna Karvonen in Beneris:
  • Impact of fish consumption on nutrient intakes
  • ‎‎Cardiovascular dose-responses of fish consumption
  • Mental health dose-responses of fish consumption
  • Immunological disease dose-responses of fish consumption
  • Diabetes and glucose dose-responses of fish consumption‎
  • Developmental dose-responses of fish consumption
  • Cancer dose-responses of fish consumption
  • Bone dose-responses of fish consumption
  • All-cause mortality dose-response of fish consumption‎