Skip to main content Accessibility help
×
Home
Hostname: page-component-78dcdb465f-2ktwh Total loading time: 0.598 Render date: 2021-04-16T03:54:37.598Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": false, "newCiteModal": false, "newCitedByModal": true }

Meat consumption and risk of type 2 diabetes: the Multiethnic Cohort

Published online by Cambridge University Press:  13 July 2010

A Steinbrecher
Affiliation:
Cancer Research Center, University of Hawaii, 1236 Lauhala Street, Honolulu, HI 96813, USA
E Erber
Affiliation:
Cancer Research Center, University of Hawaii, 1236 Lauhala Street, Honolulu, HI 96813, USA
A Grandinetti
Affiliation:
John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
LN Kolonel
Affiliation:
Cancer Research Center, University of Hawaii, 1236 Lauhala Street, Honolulu, HI 96813, USA
G Maskarinec
Affiliation:
Cancer Research Center, University of Hawaii, 1236 Lauhala Street, Honolulu, HI 96813, USA
Corresponding
E-mail address:
Rights & Permissions[Opens in a new window]

Abstract

Objective

To examine the association of meat consumption with diabetes risk in the Hawaii component of the Multiethnic Cohort and to assess effect modification by ethnicity.

Design

A prospective cohort study. Baseline information on diet and lifestyle was assessed by questionnaire. The cohort was followed up for incident cases of diabetes, which were identified through self-reports, medication questionnaires, or health plan linkages. Cox regression was used to calculate hazard ratios (HR) and 95 % confidence intervals for diabetes associated with quintile of meat consumption.

Setting

Hawaii, USA.

Subjects

A total of 29 759 Caucasian, 35 244 Japanese-American and 10 509 Native Hawaiian men and women, aged 45–75 years at baseline.

Results

During a mean follow-up time of 14 years, 8587 incident diabetes cases were identified. Intake of red meat was positively associated with diabetes risk in men (fifth v. first quintile: HR = 1·43; 95 % CI 1·29, 1·59) and women (fifth v. first quintile: HR = 1·30; 95 % CI 1·17, 1·45) in adjusted models. The respective HR for processed red meat intake were 1·57 (95 % CI 1·42, 1·75) and 1·45 (95 % CI 1·30, 1·62). The association for processed poultry was weaker than for processed red meat, and fresh poultry intake was not associated with diabetes risk. For men only, we observed significant interactions of ethnicity with the red and processed red meat associations, with Caucasians experiencing slightly higher risks than Japanese-Americans.

Conclusions

Our findings support the growing evidence that red and processed meat intake increase risk for diabetes irrespective of ethnicity and level of BMI.

Type
Research paper
Copyright
Copyright © The Authors 2010

The prevalence of type 2 diabetes mellitus is increasing worldwide; however, some ethnic groups, such as Asian-Americans or Pacific Islanders, suffer from extremely high rates compared with Caucasians(Reference McNeely and Boyko1). In the Multiethnic Cohort (MEC), diabetes incidence rates of 15·5, 12·5 and 5·8 per 1000 person-years were found for Native Hawaiians, Japanese-Americans and Caucasians, respectively(Reference Maskarinec, Erber and Grandinetti2). A higher BMI and lower education were associated with higher incidence rates. Established risk factors for diabetes are overweight, obesity and physical inactivity(Reference Adeghate, Schattner and Dunn3); still, dietary factors might play an important role. A meta-analysis on meat intake and diabetes risk concluded that particularly red meat and processed meat increase diabetes risk(Reference Aune, Ursin and Veierod4). Thus far, no prospective study has examined whether this association is modified by ethnicity. We examined the association of meat consumption (red meat, processed red meat, fresh poultry and processed poultry) with diabetes risk in men and women of Caucasian, Japanese-American and Native Hawaiian ancestry in the Hawaii component of the MEC.

Materials and methods

Study population

The MEC was designed to investigate the association between diet and cancer among different ethnic groups in Hawaii and California and detailed information on study design and recruitment can be found elsewhere(Reference Kolonel, Henderson and Hankin5). In brief, between 1993 and 1996, more than 215 000 men and women, aged 45–75 years at recruitment, enrolled by completing a mailed questionnaire on diet, demographics, medical conditions, anthropometric measures and lifestyle factors.

The Hawaiian component of the MEC comprises 103 898 participants, primarily Caucasians, Japanese-Americans and Native Hawaiians. Response rates ranged from 28 % to 51 % in the different ethnic–sex groups, and comparison with US Census data indicated that the study population represented all levels of education. For the present analysis, subjects belonging to other ethnicities (n 8797), prevalent diabetes cases (n 10 028) and unconfirmed cases (n 812) were excluded, as were subjects with missing covariate (n 6202) or dietary information (n 2537) and missing information on diabetes at follow-up or baseline (n 10), leaving 36 256 men and 39 256 women. Study protocols were approved by the Committee on Human Studies at the University of Hawaii and by the Institutional Review Board of Kaiser Permanente.

Data assessment

Incident cases of diabetes mellitus were identified by self-report in a follow-up questionnaire mailed to the participants between 1999 and 2003 (response rate in Hawaii 88 %), or via a medication questionnaire (including diabetes drugs) administered to 38 % of the MEC participants who agreed to a blood draw between 2001 and 2007, or by a linkage in 2007 with the two major health plans in Hawaii, Kaiser Permanente and Blue Cross/Blue Shield, that cover 90 % of the population in Hawaii(Reference Maskarinec, Erber and Grandinetti2). After excluding 812 self-reported cases not confirmed by a health plan, a total of 8587 incident cases were identified during a median follow-up time of 13·5 years: 2251 from the follow-up questionnaire, 996 from the medication questionnaire and 5340 through the health plans. Information on vital status of all participants is updated annually by linkage with state and national death certificates.

Dietary data were collected at baseline by a validated quantitative FFQ specifically designed for use in this multiethnic population(Reference Kolonel, Henderson and Hankin5). Nutrient intake was determined by linking food intake to an ethnic-specific food composition database developed and maintained at the Cancer Research Center of Hawaii. In a validation and calibration sub-study average correlation coefficients ranged from 0·26 to 0·57 for nutrients and from 0·57 to 0·75 for nutrient densities for the different sex–ethnic groups, indicating good validity(Reference Stram, Hankin and Wilkens6).

Food group intake was calculated as grams per day of the basic food commodities and covered single food items as well as mixed dishes. Intakes were converted to energy densities (g/4184 kJ per d). Food groups examined for the current analysis were red meat (beef, pork and lamb), fresh poultry, processed red meat and processed poultry.

Statistical analysis

We applied Cox proportional hazard regression with follow-up time as the underlying time metric and stratified by age at cohort entry to estimate hazard ratios (HR) and 95 % confidence intervals for sex-specific quintiles of meat consumption. Linear trend tests were performed using an ordinal variable representing the median of each quintile. Follow-up time was calculated as the difference between date of cohort entry and date of diabetes diagnosis, date of death or last date when data on diabetes status were available, whichever came first(Reference Maskarinec, Erber and Grandinetti2). The final models were adjusted for ethnicity, BMI, physical activity, education and energy intake (log-transformed). We tested for interaction of meat consumption and ethnicity and additionally calculated ethnic-specific HR of diabetes for meat consumption. No major violations of the proportional hazards assumption were observed when examined with time-dependent explanatory variables. All statistical analyses were performed using the SAS statistical software package version 9·2 (SAS Institute Inc., Cary, NC, USA).

Results

The median intake of beef or fresh poultry did not differ by ethnicity, but higher amounts of pork, red meat and processed red meat were consumed by Native Hawaiians, while Caucasians tended to consume least of these meat groups (Table 1).

Table 1 Baseline characteristics of participants in the Hawaii component of the Multiethnic Cohort by ethnicity and sex, 1993–2007

IQR, interquartile range; METS, metabolic equivalent of tasks.

*Nutrient intakes in g/4184 kJ per d.

Red meat and processed red meat were positively associated with diabetes risk in men (Table 2). The HR comparing extreme quintiles was 1·43 (95 % CI 1·29, 1·59) for red meat and 1·57 (95 % CI 1·42, 1·75) for processed red meat in multivariate-adjusted models. When we excluded BMI from the model, the HR for comparing extreme quintiles was 1·70 (95 % CI 1·54, 1·88) for red meat and 1·92 (95 % CI 1·73, 2·13) for processed meat. Further adjustment for fibre intake, which was recently shown to be associated with diabetes in this cohort, attenuated this association slightly with HR of 1·38 (95 % CI 1·24, 1·53) for red meat and 1·53 (95 % CI 1·37, 1·71) for processed red meat comparing highest v. lowest quintile (data not shown). Intake of fresh poultry was not associated with diabetes risk although HR for the second, third and fourth quintiles were slightly increased. Intake of processed poultry increased risk by 30 % for the highest intake quintile compared with the lowest.

Table 2 Diabetes risk as hazard ratio (HR) and 95 % confidence interval associated with quintiles of meat consumption in men, Hawaii component of the Multiethnic Cohort Study, 1993–2007

*Median intake in g/4184 kJ per d.

†HR adjusted for ethnicity, education, BMI, physical activity and total energy intake (log-transformed) as well as stratified by age at cohort entry.

Similar associations between meat intake and diabetes risk were found in women (Table 3), although the risk estimates tended to be lower than in men. HR for diabetes comparing the highest v. lowest intake quintile was 1·30 (95 % CI 1·17, 1·45) for red meat and 1·45 (95 % CI 1·30, 1·62) for processed red meat. Without adjustment for BMI, the respective HR was 1·67 (95 % CI 1·50, 1·86) and 1·84 (95 % CI 1·65, 2·06). Additional adjustment for fibre intake did not alter the multivariate-adjusted estimates: HR = 1·29 (95 % CI 1·15, 1·45) for red meat and HR = 1·45 (95 % CI 1·30, 1·65) for processed red meat (data not shown). Fresh poultry intake was not associated with diabetes, but women in the fifth quintile of processed poultry intake had a 23 % higher diabetes risk compared with the lowest quintile.

Table 3 Diabetes risk as hazard ratio (HR) and 95 % confidence interval associated with quintiles of meat consumption in women, Hawaii component of the Multiethnic Cohort Study, 1993–2007

*Median intake in g/4184 kJ per d.

†HR adjusted for ethnicity, education, BMI, physical activity and total energy intake (log-transformed) as well as stratified by age at cohort entry.

Associations for the fifth v. the first meat intake quintile stratified by ethnicity are shown in Fig. 1 for men and Fig. 2 for women. In men, the tests for interaction between ethnicity and red meat intake (P interaction = 0·006) and processed red meat intake (P interaction = 0·002) were significant, with a slightly higher risk for Caucasians and a lower risk for Japanese-Americans. We did not find a significant interaction for fresh (P interaction = 0·47) or processed poultry (P interaction = 0·46) in men or for any meat type in women (P interaction = 0·47 for processed red meat, 0·32 for fresh poultry and 0·24 for processed poultry), except for consumption of red meat with a borderline significant interaction (P interaction = 0·05).

Fig. 1 Diabetes risk (hazard ratio (HR) and 95 % confidence interval) comparing highest v. lowest quintile of meat consumption by ethnicity in men, Hawaii component of the Multiethnic Cohort Study, 1993–2007. HR adjusted for education, BMI, physical activity and total energy intake (log-transformed) as well as stratified by age at cohort entry; numbers in parentheses represent the number of diabetes cases in the highest v. lowest quintile of meat consumption

Fig. 2 Diabetes risk (hazard ratio (HR) and 95 % confidence interval) comparing highest v. lowest quintile of meat consumption by ethnicity in women, Hawaii component of the Multiethnic Cohort Study, 1993–2007. HR adjusted for education, BMI, physical activity and total energy intake (log-transformed) as well as stratified by age at cohort entry; numbers in parentheses represent the number of diabetes cases in the highest v. lowest quintile of meat consumption

Discussion

In the current analysis of the Hawaii component of the MEC, we found a positive association between intakes of red meat, processed red meat and processed poultry with risk of diabetes in men and women independent of BMI status. Fresh poultry consumption was not associated with diabetes risk.

Strengths of the present study are the large sample size, the prospective design with long follow-up time, and the extensive data collection allowing adjustment for a variety of known confounders such as BMI. However, the possibility of residual confounding cannot be excluded. The study FFQ was specifically designed for use in this multiethnic cohort, and reproducibility and validity of nutrient intake densities were found to be satisfactory and comparable to those of other similar studies(Reference Stram, Hankin and Wilkens6). Moreover, mixed dishes containing meat were disaggregated into their component ingredients and considered in the estimation of total meat intake. However, misreporting of certain foods might have biased our results, although due to the prospective design, disease status could not have influenced reporting of meat intake. Since we did not have repeat measurements of diet, changes in diet over time could not be considered in the analysis. Furthermore, we were not able to distinguish the effect of meat from intakes of its major constituents, such as animal fat, animal protein and haem Fe. Although diabetes status was ascertained by several questionnaires and linkage with health plans, information on type of diabetes was not available; however, given the median age of 59 years of the participants at baseline, more than 90 % of cases were likely to have had type 2 diabetes. Despite the comprehensive case identification approach, some MEC participants may have diabetes that has not been detected yet.

Our results agree with several prospective studies on meat intake and diabetes risk. In a recent meta-analysis(Reference Aune, Ursin and Veierod4), the summary risks comparing high v. low intake were 1·21 (95 % CI 1·07, 1·38) for red meat and 1·41 (95 % CI 1·25, 1·60) for processed meat. The magnitude of these estimates corresponds well with those from our study, although caution is needed for such comparisons due to different units in exposure measurement. Furthermore, the type of red meat consumed (i.e. beef or pork) and the proportion of poultry in comparison to red meat intake likely differs among countries. For example, in a Finnish study(Reference Montonen, Jarvinen and Heliovaara7), intakes of red meat (mean intake in non-cases: 79·6 g/d) and processed meat (52·0 g/d) were considerably higher than poultry intake (2·6 g/d), while intakes of poultry and red meat were nearly equal in our study.

A few studies have examined the association between intake of fresh poultry and diabetes risk, with one reporting no association(Reference van Dam, Willett and Rimm8) and several others observing an inverse association(Reference Montonen, Jarvinen and Heliovaara7, Reference Villegas, Shu and Gao9, Reference Schulze, Manson and Willett10). The slightly elevated risk for the second, third and fourth intake quintile might be due to chance, errors in intake measurements and close correlation between the different types of meat intake. To our knowledge, no other study has examined the association between intake of processed poultry and diabetes.

In an earlier analysis of the MEC, we found an inverse association between dietary fibre intake and diabetes risk in men but not in women(Reference Hopping, Erber and Grandinetti11). As red meat and processed red meat were negatively correlated with fibre intake, we additionally adjusted the present analysis for fibre intake to exclude the possibility of confounding. The HR for red and processed meat in men decreased slightly but remained significant, indicating an effect of meat irrespective of fibre intake. Nevertheless, one has to consider that the positive association of meat consumption and diabetes risk might not be attributable to meat intake per se, but rather to a dietary pattern like the so-called ‘Western’ pattern, which combines high meat intake, especially processed red meat and processed poultry, with refined grains and sweets(Reference Erber, Hopping and Grandinetti12).

We found no strong indication for effect modification by ethnicity. Tests for interaction were statistically significant only for red and processed red meat consumption in men, which might be explained by ethnically different meat preparation practices or differences in the choice of red meat types. However, the HR for the three ethnic groups did not differ meaningfully and thus the statistical significance might be driven more by the large sample size or the small standard deviations than an underlying biological difference.

One hypothesis for a role of meat intake in diabetes aetiology is that meat consumption increases fat intake, especially saturated fat intake, and thus might act indirectly by increasing body weight, an established risk factor for diabetes(Reference Adeghate, Schattner and Dunn3). Our analysis without adjustment for BMI supported this hypothesis. However, when adjusting for BMI, we still found a significant positive association, indicating that other mechanisms might be important. For example, heating foods such as meat can lead to high levels of advanced glycation end-products, which have been associated with inflammatory responses in human subjects(Reference Uribarri, Cai and Sandu13). Red meat is a source of haem Fe; higher body Fe stores might impair insulin sensitivity(Reference Hua, Stoohs and Facchini14) and increase the risk of diabetes(Reference Salonen, Tuomainen and Nyyssonen15) by promoting oxidative stress causing tissue damage(Reference Wolff16). Processed meat might contain preservatives, additives or other chemicals, such as nitrates, nitrites and heterocyclic amines, formed during food preparation. Nitrites, for example, might be converted to nitrosamines, which exert pancreatic β-cell toxicity(Reference LeDoux, Woodley and Patton17). Unfortunately, we had no data on food preservation methods to perform separate analysis for these compounds.

In conclusion, our findings add to the growing evidence for a positive association of red meat and processed meat intake with diabetes risk. We found this association to be consistent over the different ethnic strata of the MEC, despite the higher incidence rates of diabetes in Native Hawaiians and Japanese-Americans compared with Caucasians. Besides the known role of body weight, these results highlight the importance of diet and food choices in diabetes aetiology.

Acknowledgements

Sources of funding: The Multiethnic Cohort is supported by NCI grant R37CA54281 (Principal Investigator: Dr L.N. Kolonel). The recruitment of Native Hawaiians was funded by grant DAMD 17-94-T-4184 (Principal Investigator: Dr A. Nomura). The diabetes project is funded by R21 DK073816 (Principal Investigator: Dr G. Maskarinec). Conflicts of interest: The authors declare that there is no conflict of interest associated with this manuscript. Authorship contributions: All authors made substantial contributions to conception and design, acquisition, analysis or interpretation of data, have been part of writing or critically reviewing the article, and approved the final version. Acknowledgements: We thank Mark M. Schmidt and Aileen Uchida at Kaiser Permanente Center for Health Research, Honolulu, HI and Deborah Taira Juarez and Krista Hodges at HMSA, Blue Cross Blue Shield of Hawaii for their assistance in linking the cohort with the health plans.

References

1.McNeely, MJ & Boyko, EJ (2004) Type 2 diabetes prevalence in Asian Americans: results of a national health survey. Diabetes Care 27, 6669.CrossRefGoogle ScholarPubMed
2.Maskarinec, G, Erber, E, Grandinetti, A et al. (2009) Diabetes incidence based on linkages with health plans: the Multiethnic Cohort. Diabetes 58, 17321738.CrossRefGoogle ScholarPubMed
3.Adeghate, E, Schattner, P & Dunn, E (2006) An update on the etiology and epidemiology of diabetes mellitus. Ann N Y Acad Sci 1084, 129.CrossRefGoogle ScholarPubMed
4.Aune, D, Ursin, G & Veierod, MB (2009) Meat consumption and the risk of type 2 diabetes: a systematic review and meta-analysis of cohort studies. Diabetologia 52, 22772287.CrossRefGoogle ScholarPubMed
5.Kolonel, LN, Henderson, BE, Hankin, JH et al. (2000) A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics. Am J Epidemiol 151, 346357.CrossRefGoogle ScholarPubMed
6.Stram, DO, Hankin, JH, Wilkens, LR et al. (2000) Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles. Am J Epidemiol 151, 358370.CrossRefGoogle ScholarPubMed
7.Montonen, J, Jarvinen, R, Heliovaara, M et al. (2005) Food consumption and the incidence of type II diabetes mellitus. Eur J Clin Nutr 59, 441448.CrossRefGoogle ScholarPubMed
8.van Dam, RM, Willett, WC, Rimm, EB et al. (2002) Dietary fat and meat intake in relation to risk of type 2 diabetes in men. Diabetes Care 25, 417424.CrossRefGoogle ScholarPubMed
9.Villegas, R, Shu, XO, Gao, YT et al. (2006) The association of meat intake and the risk of type 2 diabetes may be modified by body weight. Int J Med Sci 3, 152159.CrossRefGoogle ScholarPubMed
10.Schulze, MB, Manson, JE, Willett, WC et al. (2003) Processed meat intake and incidence of type 2 diabetes in younger and middle-aged women. Diabetologia 46, 14651473.CrossRefGoogle ScholarPubMed
11.Hopping, BN, Erber, E, Grandinetti, A et al. (2010) Dietary fiber, magnesium, and glycemic load alter risk of type 2 diabetes in a multiethnic cohort in Hawaii. J Nutr 140, 6874.CrossRefGoogle Scholar
12.Erber, E, Hopping, BN, Grandinetti, A et al. (2010) Dietary patterns and risk for diabetes: the Multiethnic Cohort. Diabetes Care 33, 532538.CrossRefGoogle ScholarPubMed
13.Uribarri, J, Cai, W, Sandu, O et al. (2005) Diet-derived advanced glycation end products are major contributors to the body’s AGE pool and induce inflammation in healthy subjects. Ann N Y Acad Sci 1043, 461466.CrossRefGoogle ScholarPubMed
14.Hua, NW, Stoohs, RA & Facchini, FS (2001) Low iron status and enhanced insulin sensitivity in lacto-ovo vegetarians. Br J Nutr 86, 515519.CrossRefGoogle ScholarPubMed
15.Salonen, JT, Tuomainen, TP, Nyyssonen, K et al. (1998) Relation between iron stores and non-insulin dependent diabetes in men: case–control study. BMJ 317, 727730.CrossRefGoogle ScholarPubMed
16.Wolff, SP (1993) Diabetes mellitus and free radicals. Free radicals, transition metals and oxidative stress in the aetiology of diabetes mellitus and complications. Br Med Bull 49, 642652.CrossRefGoogle ScholarPubMed
17.LeDoux, SP, Woodley, SE, Patton, NJ et al. (1986) Mechanisms of nitrosourea-induced β-cell damage. Alterations in DNA. Diabetes 35, 866872.CrossRefGoogle ScholarPubMed

Altmetric attention score

Full text views

Full text views reflects PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.

Total number of HTML views: 266
Total number of PDF views: 647 *
View data table for this chart

* Views captured on Cambridge Core between September 2016 - 16th April 2021. This data will be updated every 24 hours.

You have Access

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Meat consumption and risk of type 2 diabetes: the Multiethnic Cohort
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Meat consumption and risk of type 2 diabetes: the Multiethnic Cohort
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Meat consumption and risk of type 2 diabetes: the Multiethnic Cohort
Available formats
×
×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *