Is Fried Fish Good For Diabetes? A Closer Look

Find more work by 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden

Find more work by 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden

Find more work by 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden

Find more work by 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden

2The Institute of Metabolic Science at the University of Cambridge School of Clinical Medicine in Cambridge, UK, is part of the Medical Research Council Epidemiology Unit.

Find more work by 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden

Different parts of the world have different types of epidemiological evidence on the link between eating fish and the risk of type 2 diabetes. Differences related to fish consumption pattern could possibly help explain the discrepancy between the findings. So, we wanted to look into the link between eating fish (all types, fried fish, and certain types of fish) and getting type 2 diabetes, taking into account the contaminants found in fish (polychlorinated biphenyls and methyl mercury).

The population-based Cohort of Swedish Men, including 35,583 men aged 45–79 years, was followed from 1998 to 2012. We estimated hazard ratios (HRs) with 95 % confidence intervals (CIs) using Cox proportional hazards models.

During 15 years of follow-up, 3624 incident cases were identified. Total fish consumption (≥4 servings/week vs. <1 serving/week) was not associated with type 2 diabetes in multivariable-adjusted analysis (HR 1. 00; 95 % CI 0. 85–1. 18); however, a statistically non-significant inverse association was observed after adjustment for dietary contaminant exposures (HR 0. 79; 95 % CI 0. 60–1. 04). Fried fish (≥6 servings/month vs. ≤1 servings/month) and shellfish consumption (≥1 serving/week vs. never/seldom) were associated with HRs of 1. 14 (95 % CI 1. 03–1. 31) and 1. 21 (95 % CI 1. 07–1. 36), respectively.

We observed no overall association between total fish consumption and type 2 diabetes. The results indicated that dietary contaminants in fish may influence the relationship. Fried fish and shellfish consumption were associated with higher type 2 diabetes incidence. Based on these results, it may be necessary to give more detailed information on different types of fish (with different levels of contamination) and how to prepare them.

The online version of this article (doi:10.1007/s00394-015-1132-6) contains supplementary material, which is available to authorized users.

Type 2 diabetes is a growing public health burden, and the prevalence has reached epidemic proportions globally [1]. People think that eating fish might help protect against type 2 diabetes because it is good for lowering the risk of heart disease and other heart diseases [2]. However, epidemiological studies that looked at the link between eating fish and the risk of getting diabetes didn’t come to any clear conclusions [3–16]. Several meta-analyses have shown that the results are not all the same and that there may be geographical differences. For example, studies done in Asia found negative associations, while studies in Europe found no overall associations and studies in the US found higher risks [17–19]. Differences in fish consumption pattern potentially determined by geographical location (e. g. different types of fish eaten, how it was prepared, and the level of contamination could help explain the difference in results. However, these factors have not been fully considered in previous studies that looked at the link between eating fish and the risk of type 2 diabetes. Fish fried in oil might be important because it creates AGEs [20], mutagenic compounds [21], changes in the makeup of fatty acids, or higher energy density. Also, studies that separate fried fish from non-fried fish showed that the links may be different depending on how the fish is prepared [22–26]. Contaminants present in fish may also be of importance. Many people get persistent organic pollutants like polychlorinated biphenyls (PCBs) [27] and methyl mercury (MeHg) [28] from eating fish. These pollutants have been linked to type 2 diabetes [29, 30]. So, we wanted to look into the link between eating a lot of fish, fried fish, and certain types of fish with getting type 2 diabetes in a large population-based prospective study that took into account the contaminants that are found in fish.

The Cohort of Swedish Men is a prospective population-based study initiated in the autumn of 1997. Men born between 1918 and 1952 (45–79 years old) who lived in the central Swedish counties of Örebro and Västmanland were invited to take part in the study and given a questionnaire about their diet and other aspects of their lifestyle. A total of 48,850 men returned the questionnaire (response rate 49 %). The response rate for an extended health questionnaire sent out in 2008 (70%) was 10%. The questionnaire included a question about diabetes status. The group is typical of Swedish men aged 45 to 79 in terms of age distribution, level of education, and the number of overweight men [31]. The study was approved by the Regional Ethical Review Board at Karolinska Institutet (Stockholm, Sweden). Sending back the completed questionnaire was seen as proof of knowing what was being studied.

We took out of the baseline population the 205 men whose national identification number was wrong or incomplete, the 92 men who sent back a questionnaire that wasn’t fully filled out, and the 55 men who died or were diagnosed with cancer (not including non-melanoma skin cancer; n = 2592) before January 1, 1998. We also took out common cases of diabetes based on data from the Swedish National Diabetes Register (NDR) and the Swedish National Patient Register (NPR), as well as self-reports from the start (n = 3404) Also, we didn’t include people who said they had diabetes in the 2008 questionnaire but the registry data couldn’t confirm it (n = 67) or people who were registered with non-type 2 diabetes during the follow-up period (n = 200). Also, people who had a history of CVD (myocardial infarction, angina, or stroke; n = 4537) were not included because they might have changed what they ate after being diagnosed and so that the results could be compared with those from other studies. We also didn’t count people whose total energy intake numbers didn’t make sense (±3 SD from the log-transformed mean energy intake; n = 398), people who didn’t answer any of the questions on the questionnaire about fish intake (n = 239), or people who didn’t give us enough information about how often they fried (n = 1478). After these exclusions, 35,583 men remained for analysis.

Assessment of diet and covariates

At the start of the study, a 96-item food frequency questionnaire (FFQ) was used to measure dietary intake. Participants were asked to rate how often they had eaten different foods on average over the previous year. Eight frequency groups were used: never or rarely; once to three times a month; once to two times a week; three to four times a week; five to six times a week; once a day; twice a day; or more than three times a day. When it came to eating fish, people were asked to rate how often they ate three types of finfish (herring/mackerel, salmon/whitefish/char, cod/saithe/fish fingers), as well as shellfish (shrimp/crayfish, etc.). ). Partial non-response in the fish intake section was assumed to imply never/seldom. This was based on a study of Swedish men and women that showed that 28% of the answers that were left out about fish consumption were consistent with not eating fish [32]. To get an idea of how much fish people eat overall, the middle number of the frequency range for each type of fish was turned into servings per week and added up. This was done for herring, mackerel, salmon, whitefish, char, cod, saithe, and fish fingers. In a separate, open section of the questionnaire, participants were asked to say how often they ate fried fish every month. There were no predefined frequency categories.

The total amount of energy that people in four age groups (≤52, 53–61, 62–69, and ≥70 years) ate was figured out by looking at two weighted diet records that 152 men filled out over the course of one week. Food composition values were obtained from the Swedish National Food Agency Database [33].

The validity of the FFQ has been assessed in a random sample of 248 men aged 40–74 years. The Spearman correlation coefficients between FFQ-based estimates and the average of 14 24-hour recall interviews that were done 14 times over the course of a year were 0. 65 for macronutrients and 0. 62 for micronutrients [34]. A validation study of the FFQ looked at 129 women from the same study area who were the same age. The results showed that the estimates from the FFQ and four weighted diet records for one week were most often in line with each other. 4 to 0. 6 for fish and shellfish items (A. Wolk, unpublished data).

We used a quality score instead of several single food groups to account for the overall diet and cut down on the number of covariates in the models. We used the score suggested by Fung et al. to figure out a DASH (Dietary Approaches to Stop Hypertension) diet component score as an overall dietary quality score. [35], which ranks participants according to their intake of eight dietary components. If you ate a lot of fruits, vegetables, nuts, and legumes, as well as low-fat dairy and whole grains, and not much sodium, sugary drinks, red meat, or processed meat, you got higher scores.

For FFQ-based estimates of PCB and MeHg exposure from food, we used recipe-based databases made for the FFQ. The PCB database, which is explained in more detail elsewhere [27], was based on the PCB congener 153, which is the most common congener in Swedish food and a great way to find out how much PCB is in blood, fat, and food [36, 37]. Concentrations of PCBs and MeHg in foods were gotten from the Swedish National Food Agency and the Swedish Environmental Protection Agency. Dietary exposure estimates were made by looking at how often and how much of each food people of different ages ate. For each food item in the FFQ, the contaminant calculations were based on a larger number of specific food types that were chosen based on how people in the population eat. The exposure estimates were adjusted to the mean energy intake in the cohort using the residual method [38]. Fish and shellfish contributed to about 2/3 of the total dietary PCB exposure in the cohort. Dietary MeHg exposure was estimated based only on fish and shellfish because that’s pretty much the only source of MeHg in food, with lean fish species making up about 20% of the cohort. The estimates of long-term PCB exposure from food were largely consistent with the total amount of 6 PCB congeners found in serum [correlation (r), 0]. 48; p < 0. 001] in a sample of 201 Swedish women [27]. Hair mercury levels in a Swedish population are strongly linked to the amount of fish people eat (r = 0.04). 75; p < 0. 001) [28].

On the baseline questionnaire, people were asked about their height, weight, education, drinking, smoking, and physical activity. Body mass index (BMI) was calculated by dividing weight (in kg) by the square of height (in m). For total physical activity, the amount of time people said they spent each day on different activities (like work/occupational activity, home/household work, walking/bicycling, watching TV/reading, exercising, and sleeping) was multiplied by the amount of energy those activities usually used (in metabolic equivalents, METs), and the result was a MET-h/day score [39].

Case ascertainment and follow-up of the cohort

Study participants were followed from 1 January 1998 to 31 December 2012. The study group was linked to the Swedish National Diabetes Register (NDR) and the Swedish National Patient Register (NPR), which found cases of type 2 diabetes. The NDR has been around since 1996 and has clinical information from visits to patients that are reported at least once a year. It also keeps track of the year that diabetes started in the past. Based on how common diabetes is thought to be, NDR coverage is thought to be almost complete in the study area [40]. In the validation against the Swedish Prescribed Drug Register, more than 90% of people aged 20 to 94 years who were taking diabetes medication were covered by NDR [40]. The NPR needs to be told about all inpatient and outpatient care visits in Sweden since 1987, as well as information on the main and secondary diagnoses for both private and public caregivers since 2001. ICD-10 code E11 was used to identify cases of type 2 diabetes. The first available date in either of the two registers was considered as the diagnosis date. Dates of death were obtained from the Swedish Death Register.

We used Cox proportional hazards regression models to find the hazard ratios (HRs) and confidence intervals (CIs) for the relationships between total fish consumption (including herring/mackerel, salmon/whitefish/char, and cod/saithe/fish fingers), fried fish consumption, specific fish items, and the incidence of type 2 diabetes. Total fish was categorized in five groups (<1, 1–<2, 2–<3, 3–<4 and ≥4 servings/week). Of note, the recommended fish consumption in Sweden, 2–3 servings/week, is represented in the mid-category. Overall, the categorization reflects the consumption pattern in the study population. As the number of participants reporting no fish consumption was small (n = 911; 2. 6 %), we also included low consumers in the reference category. Still, to see how strong our results were, we did more tests using only people who don’t eat fish as the reference group. For the categorization of fried fish consumption, we used approximate quintiles (≤1, 2, 3–4, 5, ≥6 servings/month). Each fish item was put into one of three groups: never or rarely, 1–3 servings/month, or ≥1 serving/week. The first two groups were based on the FFQ’s two lowest frequency categories, and the third group was made up of the six highest response categories. Age was used as underlying timescale in all analyses. Every person who took part gave person-time from January 1, 1998, until they were diagnosed with type 2 diabetes, died, or the study ended, whichever came first.

The primary multivariable analyses were adjusted for BMI (kg/m2; <20, 20–24. 9, 25–29. 9 to 30 cigarettes a day, physical activity (MET-h/day; quartiles), education (primary school, high school, university), and smoking (never, used to smoke, or currently 10 cigarettes a day or more). Analyses of specific fish items were mutually adjusted for the other three types. Multivariable model 2 was further adjusted for dietary exposure to PCBs (ng/day, quintiles) and MeHg (µg/day, quintiles). Missing values for any covariates were treated as a separate category in the model. The Schoenfeld residual test indicated no violation of the proportional hazard assumption. To check for a linear trend, the median value for each participant’s exposure category was given to them and modeled as a continuous variable. We looked at the dose-response relationship between eating fried fish and HR of type 2 diabetes using restricted cubic splines with knots at 2010, 2005, and 90% of the distribution. We found the p value for nonlinearity by testing the idea that the second spline’s coefficient is equal to 0.

As a safety measure, we left out men who said they took fish oil supplements (n = 1649; 4%). 6 % of the study population).

Statistical analyses were carried out using Stata (version 13.0), and p values ≤0.05 were considered statistically significant.

During 15 years of follow-up (467,961 person-years), 3624 incident cases of type 2 diabetes were identified. The mean (±SD) number of servings consumed per week was 0. 6 (±0. 8) of herring/mackerel, 0. 4 (±0. 9) of salmon/whitefish/char, 0. 9 (±1. 0) of cod/saithe/fish fingers and 0. 4 (±0. 6) of shellfish. The mean frequency of consuming fried fish was 3. 2 (±2. 9) times/month. The mean energy-adjusted dietary exposure to PCBs was 274 (±191) ng/day and to MeHg 1. 5 (±1. 3) µg/day.

Age-standardized baseline characteristics by total fish consumption are presented in Table . A study found that men who ate more fish had higher energy intake and higher intake per 1000 kcal of fruit, vegetables, nuts and legumes, and lower intake of low-fat dairy. These men were also slightly older and more likely to have gone to college.

Categories of total fish consumption, servings/week (median)
<1 (0.9)	1–<2 (1.4)	2–<3 (2.4)	3–<4 (3.5)	≥4 (5.0)
No. of participants	10,867	13,458	6292	3367	1599
Age (mean ± SD, years)	58.8 ± 9.4	59.1 ± 9.2	58.7 ± 9.2	62.2 ± 9.6	62.7 ± 9.7
BMI (mean, kg/m2)	26	26	25	26	26
Total physical activity (mean, MET-h/day)	42	42	41	42	42
University education (%)	14	18	23	21	22
Current smokers (%)	27	24	20	25	27
Alcohol (mean, g/day)	15	15	16	17	21
Energy intake (mean, kcal/day)	2529	2689	2861	2922	3263
Fried fish (mean, servings/month)	2.5	3.2	3.6	4.3	4.8
Dietary components (mean, g/1000 kcal)
Fruits	63	68	76	75	80
Vegetables	45	53	60	61	68
Nuts and legumes	16	17	19	21	26
Whole grains	78	81	82	85	79
Low-fat dairy	116	114	113	108	101
Sodium	1.4	1.4	1.5	1.5	1.6
Red and processed meats	38	40	40	40	45
Sweetened beverages	77	72	62	65	62
Dietary PCB exposure (mean, ng/day)a	162	241	314	442	776
Dietary MeHg exposure (mean, µg/day)a	0.7	1.4	1.9	2.4	4.1

Table shows HRs with 95 % CIs for type 2 diabetes by categories of total fish consumption. There was no link found when the data was adjusted for age or when BMI, physical activity, education, smoking, drinking, and diet were all taken into account. Once more contaminants were taken into account, there was a statistically non-significant negative link between people who ate ≥4 servings/week and people who ate 79; 95 % CI 0. 60–1. 04). When never/seldom consumers (n = 911) were used as the reference, the results were the same in both the primary model (HR 0 94; 95 % CI 0. 73–1. 21) and in the contaminant-adjusted model (HR 0. 75; 95 % CI 0. 52–1. 07). Dietary PCB and MeHg exposure had a similar effect on the link between eating fish and getting diabetes, but neither of them was significantly linked to getting type 2 diabetes (HRs, 1). 07 (95 % CI 0. 90–1. 26; p trend = 0. 41) and 1. 14 (95 % CI 0. 95–1. 36; p trend = 0. 06) for PCB and MeHg, respectively, comparing extreme quintiles.

Categories of total fish consumption, servings/week (median)					p for trend
<1 (0.9)	1–<2 (1.4)	2–<3 (2.4)	3–<4 (3.5)	≥4 (5)
No. of cases	1104	1363	609	378	170
Person-years	142,599	178,573	84,243	42,606	19,940
Age-adjusted model	1.00 (ref)	0.97 (0.90–1.05)	0.93 (0.84–1.03)	1.06 (0.94–1.19)	1.01 (0.86–1.19)	0.67
Multivariable modela	1.00 (ref)	1.02 (0.95–1.11)	1.01 (0.91–1.12)	1.10 (0.98–1.24)	1.00 (0.85–1.18)	0.48
Multivariable model 2 (+contaminants)b	1.00 (ref)	0.95 (0.84–1.07)	0.86 (0.72–1.03)	0.89 (0.71–1.12)	0.79 (0.60–1.04)	0.13

Taking out the first two years of follow-up (305 cases diagnosed in 1998–1999) from the main analysis didn’t change the links that were already seen (≥4 servings/week vs. <1 serving/week of total fish, model 1: HR 1. 01; 95 % CI 0. 85–1. 20; model 2: HR 0. 79; 95 % CI 0. 59–1. 05).

The Spearman correlation between total fish consumption and quintiles of dietary contaminant exposure was 0. 77 for PCB and 0. 70 for MeHg. To see what might happen when we statistically adjust collinear variables, we looked at the link between total fish consumption (divided into Compared to men who eat a lot of fish, 91; 95 % CI 0. 69–1. 22) and above the median (multivariable HR 0. 87; 95 % CI 0. 70–1. 09). The corresponding HRs for men below and above the median dietary MeHg exposure were 1. 02 (95 % CI 0. 83–1. 25) and 0. 91 (95 % CI 0. 75–1. 10).

Fried fish consumption (≥6 servings/month vs. ≤1 serving/month) was associated with higher incidence of type 2 diabetes (HR 1. 14; 95 % CI 1. 03–1. 31) in the multivariable model (Table ). Further adjustment for the contaminants did not markedly alter these results (HR 1. 13; 95 % CI 1. 00–1. 28). We didn’t find any evidence of a nonlinear link between eating fried fish and getting type 2 diabetes in the restricted cubic spline model (p nonlinearity = 0). 21). Each one serving/week increment in fried fish consumption was associated with an HR of 1. 07 (95 % CI 1. 02–1. 11).

Categories of fried fish consumption, servings/month (median)					p for trend
≤1 (0)	2 (2)	3–4 (4)	5 (5)	≥6 (8)
No. of cases	779	624	1359	435	427
Person-years	118,221	85,359	165,762	50,258	48,361
Age-adjusted model	1.00 (ref)	1.10 (0.99–1.23)	1.20 (1.10–1.31)	1.29 (1.15–1.45)	1.25 (1.11–1.41)	<0.001
Multivariable modela	1.00 (ref)	1.08 (0.97–1.20)	1.15 (1.05–1.26)	1.16 (1.03–1.31)	1.14 (1.03–1.31)	0.004
Multivariable model 2 (+ contaminants)b	1.00 (ref)	1.08 (0.97–1.21)	1.15 (1.05–1.26)	1.16 (1.03–1.30)	1.13 (1.00–1.28)	0.01

There were no links found between the three types of finfish on their own (Supplementary table), but eating shellfish (≥1 serving/week vs. never/seldom) was associated with higher type 2 diabetes incidence (HR 1. 21; 95 % CI 1. 07–1. 36) in the multivariable model (Table ). When dietary PCB and MeHg exposure were taken into account, the point estimates for all finfish types were slightly lowered, but the associations were still not statistically significant. The association with shellfish was not markedly influenced (HR 1. 19; 95 % CI 1. 04–1. 35).

Categories of shellfish consumption (median)			p for trend
Never/seldom	1–3 servings/month	≥1 serving/week (1.5)
No. of cases	1006	2161	457
Person-years	128,943	286,299	52,719
Age-adjusted model	1.00 (ref)	1.05 (0.97–1.13)	1.21 (1.08–1.35)	0.001
Multivariable modela	1.00 (ref)	1.12 (1.03–1.22)	1.21 (1.07–1.36)	0.003
Multivariable model 2 (+contaminants)b	1.00 (ref)	1.12 (1.03–1.22)	1.19 (1.04–1.35)	0.01

Leaving out fish oil supplement users (n = 1649; 178 cases) didn’t change the multivariable-adjusted estimates that compared the highest vs. lowest categories of consumption (total fish: HR 1. 03; 95 % CI 0. 87–1. 22, fried fish: HR 1. 11; 95 % CI 0. 98–1. 25, shellfish: HR 1. 18; 95 % CI 1. 05–1. 34).

In this large group of men, there was no overall link between the amount of fish eaten and the risk of getting type 2 diabetes. This was not a statistically significant link, though, when dietary exposure to PCBs and MeHg contaminants found in fish was taken into account. Consuming fried fish and shellfish was linked to a higher risk of type 2 diabetes. These links were not significantly changed when additional contaminants were taken into account.

Previous cohort studies that looked at how much fish people eat and their risk of getting type 2 diabetes came to different conclusions. Three studies [6, 12, 13] found inverse associations, eight studies [3, 4, 9, 10, 14–16, 41] found no associations, and three studies [5, 7, 11] found direct associations. There have been six studies that specifically looked at shellfish consumption and found mixed results. These studies found an inverse [13], direct [6], or no association [5, 7, 12, 41] between shellfish consumption and type 2 diabetes risk. Five cohort studies looked at the differences between lean and fatty fish. One found a weak negative association with fatty fish but not with lean fish [41], another found a higher risk associated with lean fish but not with fatty fish [7], a third found an negative association with lean fish but not with fatty fish [14], and the last two did not find any statistically significant associations [6, 12].

Few previous studies have taken preparation methods into account. Only one study investigated fried fish consumption, showing no association comparing ≥1 vs. <1 serving/week, whereas an inverse association with type 2 diabetes risk was observed for total fish [6]. In a different study, a direct link found for total fish consumption was weakened when fried fish intake was taken into account [7]. Different populations may have different patterns and habits when it comes to eating fish, like how often they fry it. This could help explain why different studies have different results about the link between fish and diabetes. In our study population, 40 % of the total fish consumed was fried. Researchers have found a link between eating a lot of fried foods and getting type 2 diabetes [42], being overweight or obese [43, 44], having high blood pressure [44], and getting the metabolic syndrome [45]. Studies have found that eating non-fried fish lowers your risk of heart failure [23, 26], ischaemic heart disease [22], stroke [24], and atrial fibrillation [25]. However, eating a lot of fried fish has been linked to a higher risk or no risk at all. Foods that are fried absorb more fat, which makes them higher in calories and may lead to a higher overall fat intake. The fatty acid makeup of the food also changes. For example, depending on the type of fat used to fry the fish, it may lose long-chain omega-3 fatty acids and gain other fatty acids [46]. Moreover, high-temperature cooking, such as frying, induces formation of AGEs, which may contribute to insulin resistance [20]. Frying may further contribute to the formation of mutagenic compounds, such as heterocyclic amines [21]. We cannot, however, exclude that frying is a marker for other “unhealthy” behaviours that are unmeasured.

We believe this is the first study to look at the effects of eating fish while taking into account PCB and MeHg exposure. There was a strong link between eating fish and being exposed to dietary contaminants, which could make the confidence intervals bigger and the results less accurate [47]. However, adjustment for the contaminants did not markedly inflate confidence intervals. The study’s large sample size and mostly similar results across different levels of dietary PCB and MeHg exposure are also signs that the adjustment did not lead to false results in multivariable-adjusted model 2. A recent review of prospective studies on plasma or serum PCBs and the risk of getting diabetes found that higher levels of total PCBs were linked to a higher risk [29]. Prospective studies on hair or toenails that tested for mercury have found a higher risk [30] or no link with diabetes [15, 48]. Because contaminant levels in seafood vary from place to place [49, 50], it’s possible that PCBs, MeHg, or other contaminants are partly to blame for the mixed results about the link between eating fish and the risk of getting diabetes. Researchers who looked at PCB levels in blood or serum found that people from parts of Asia and Africa had much lower levels than people from parts of Europe and the USA [51]. It didn’t change the direct link seen for eating shellfish when PCB and MeHg levels in the food were taken into account. A potential explanation for the association with shellfish could be related to how shellfish is consumed, i. e. , in Sweden often with mayonnaise or other fatty condiments.

Long-chain n-3 fatty acids may help people with insulin resistance and type 2 diabetes because they stop inflammatory pathways and turn on peroxisome proliferator-activated receptors [52]. A lot of randomized controlled trials that looked at how taking extra long-chain n-3 fatty acids affected insulin sensitivity, however, found no effects [53]. And eating fish, ob

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