Type 2 diabetes mellitus (T2DM) is one of the most prevalent chronic metabolic disorders worldwide, as well as a major risk factor for CVD(Reference Chatterjee, Khunti and Davies1). T2DM is characterised by impaired insulin sensitivity and secretion, contributing to glucose, lipid and protein metabolism dysfunction. This further explains the common features of the disease, including metabolic disorders and long-term macrovascular complications, such as atherosclerosis, CHD and cardiomyopathy(Reference Chatterjee, Khunti and Davies1). Among adults with T2DM, heart disease mortality rates are 2–4 times higher than in adults without diabetes, with CVD accounting for up to 65 % of all-cause mortality(Reference Benjamin, Blaha and Chiuve2).
Accumulating evidence indicates that an unhealthy diet and sedentary lifestyle can lead to T2DM incidence, cardiovascular morbidity or mortality and other physiological outcomes in patients with cardiometabolic risk factors by mediated low-grade systemic inflammation(Reference Loef and Walach3). Studies have found that consuming refined grains, added sugar, red meat and Fe-containing foods can lead to elevated levels of pro-inflammatory mediators in adipose tissue, including IL-1, IL-6, IL-8, TNF-α and C-reactive protein; these inflammatory factors may contribute to the pathogenesis of T2DM and metabolic dysfunction-related diseases(Reference Minihane, Vinoy and Russell4). Conversely, some dietary components, such as cereal fibre, whole-grain foods, legumes, low-fat dairy products, fruits and green leafy vegetables may protect against chronic disorders(5). Furthermore, unhealthy lifestyles such as excessive smoking, alcohol consumption and physical inactivity are associated with a higher risk of all-cause mortality from CVD among patients with T2DM(Reference Han, Cao and Feng6).
Recently, Byrd et al.(Reference Byrd, Judd and Flanders7) validated the weighted dietary inflammation score (DIS) and lifestyle inflammation score (LIS), which considered all lifestyle characteristics that may involve in the development of low-grade inflammation systemic. Inflammation-related factors such as diet, obesity, physical activity, smoking and alcohol consumption are included in the dietary and lifestyle inflammation score (DLIS), which provides an overview of how diet and lifestyle can influence inflammatory status. Since chronic disease is largely influenced by low-grade systemic inflammation(Reference Kälsch, Scharnagl and Kleber8), focusing on dietary and lifestyle components may provide a more comprehensive understanding of the relationship between lifestyle and the risk of chronic disorders than focusing on one factor like diet or obesity alone.
Most previous studies have assessed the association of DIS and LIS with the risk of chronic diseases, such as CVD risk factors and cancers in Western populations(Reference Li, Gao and Byrd9,Reference Byrd, Bostick and Judd10) . In the Tehran Lipid and Glucose Study, Teymoori et al.(Reference Teymoori, Farhadnejad and Mokhtari11) investigated the associations between these indices and diabetes incidence among Tehranian adults. To our knowledge, no research has investigated the association between DIS and LIS, and T2DM, and cardiometabolic risk factors in a region with a less industrialised lifestyle. It is important to determine whether or not the risk of lifestyle change and its association with chronic diseases (such as diabetes) is perceived in the less industrialised population. Therefore, we examined the association of whole foods-based 19-component DIS and 3-component LIS (comprising BMI, physical activity and current smoking status) with T2DM and cardiometabolic risk factors in a less industrialised lifestyle area of the Persian Cohort Study.
Methods
Study design and population
We conducted the present study among participants in the baseline phase of the Sabzevar Persian Cohort Study (SPCS). SPCS is one of the nineteen cohort sites across different parts of Iran that are involved in an ongoing Prospective Epidemiological Research Studies in Iran (PERSIAN) cohort study. The PERSIAN cohort study aims to recruit and follow 180 000 Iranian adults aged 35–75 years. Previous publications have described the PERSIAN cohort’s design, objectives, characteristics and methodology(Reference Eghtesad, Mohammadi and Shayanrad12,Reference Poustchi, Eghtesad and Kamangar13) . A more detailed description of the PERSIAN cohort can be found at http://persiancohort.com. The first phase of the SPCS was conducted from 2014 to 2017. In total, 4218 eligible participants aged 35–75 years of permanent Sabzevar residents were recruited. This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the ethics committee of the Ministry of Health and Medical Education of Iran and the Sabzevar University of Medical Science (approval number: IR.MEDSAB.REC.1400·185). Written informed consent was obtained from all subjects.
In this study, individuals with T2DM were diagnosed at baseline based on self-reported diabetes, fasting blood glucose levels ≥ 126 mg/dl or taking diabetic medicines(14,Reference Saudek, Herman and Sacks15) . Participants with a history of liver disease (n 603), kidney disease (n 36), CVD (n 308), lung disease (n 103), cancers (n 48) and current consumption of alcohol (n 294) were excluded from the study. We also excluded pregnant and lactating women (n 7), participants with missing demographic and medical data (n 25), who with more than thirty missing responses to the 115-item FFQ (n 52) and participants their reported average daily total energy intakes considered as outliers (n 10). In total, 2732 subjects were included in the analysis (Fig. 1).
Fig. 1. Participant flow chart.
Data collection
Demographic factors
In accordance with the PERSIAN cohort study protocol, demographics, socio-economic status, lifestyle characteristics (age, sex, marriage, education level, occupation, physical activity and habits of smoking and drinking alcohol), anthropometric variables, reproductive status, medication use and medical histories of individuals and families (e.g. CVD, diabetes and cancer) were collected through face-to-face interviews administered by trained practitioners using structured questionnaires.
Anthropometric measurements
Height and body weight measurements were conducted using a Seca 204 stadiometer and a calibrated 755 scale (Seca), with an accuracy of 0·1 cm and 0·1 kg, respectively. The BMI was calculated by multiplying the weight (kg) by the height squared (m2). Hip and waist circumferences (WC) were measured to the nearest 0·1 cm using an inelastic plastic tape measure while standing with feet shoulder-width apart. The waist-to-hip ratio (WHR) was calculated using the formula: WC (cm)/hip circumference (cm).
Biochemical measurements
Laboratory measurements were performed to determine serum concentrations of total cholesterol, TAG, HDL-cholesterol, LDL-cholesterol, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, γ-glutamyl transferase and fasting blood sugar. Each participant’s peripheral venous blood samples (20 ml) were drawn after fasting for 12 h, centrifuged and frozen immediately at –20°C for further analysis in Sabzevar Medical University’s central laboratory. Routine enzymatic assays were used to measure serum concentrations of lipid profile including total cholesterol, TAG, LDL-cholesterol and HDL-cholesterol. Photometric methods were used to measure liver enzyme concentrations such as alanine aminotransferase, aspartate aminotransferase, γ-glutamyl transferase and alkaline phosphatase. In addition, glucose oxidase was used to determine the serum concentration of fasting blood sugar. The biochemical tests were performed with Pars Azmoon Kits (Pars Azmoon, Inc.) with intra- and inter-assay coefficients ≤ 4·3 % on an autoanalyser (BT 1500, Biotecnica Instruments Spa).
Blood pressure assessment
Systolic and diastolic blood pressure were measured after 10 min of rest in the non-dominant arm. A trained individual took four measurements while participants were seated with their forearms at the level of the hearts using a mercury sphygmomanometer (ALPK1). A mean of four measurements was used to determine each participant’s systolic and diastolic blood pressure.
Physical activity
Physical activity information was collected using the short form of the International Physical Activity Questionnaire, previously validated in the Iranian population(Reference Moghaddam, Aghdam and Jafarabadi16). Based on questionnaire responses, physical activity expenditures were calculated as metabolic equivalent task (MET) hours per day (MET-h/d).
Dietary assessment
Face-to-face interviews were conducted by trained nutritionists to assess dietary intake using a 115-item semi-quantitative FFQ that included standard serving sizes, foods common to Iranian diets and local foods. FFQ reliability and validity have previously been reported in a healthy Iranian population(Reference Malekshah, Kimiagar and Saadatian-Elahi17). The five answers that covered consumption quantity include daily, weekly, monthly, yearly and rarely/never and were based on the Iranian population’s standard portion sizes(Reference Malekshah, Kimiagar and Saadatian-Elahi17). Lastly, the frequency of each food item was converted to g/d using ‘household measures’.
Dietary inflammation score, lifestyle inflammation score and dietary and lifestyle inflammation score calculations
We calculated the FFQ-based DIS and lifestyle questionnaire-based LIS for each participant using the methods presented by Byrd et al.(Reference Byrd, Judd and Flanders7) The DIS includes nineteen food components (eighteen whole foods and beverages, along with one composite micronutrient supplement group), which may affect the concentration of pro-inflammatory biomarkers such as IL-6, IL-8, C-reactive protein, as well as anti-inflammatory biomarkers such as IL-10. The inflammatory potential of each component was scored based on its ability to decrease or increase the levels of pro- and anti-inflammatory markers. The DIS includes leafy greens and cruciferous vegetables, tomatoes, apples and berries, deep yellow or orange vegetables and fruits, other fruits and real fruit juices, other vegetables, legumes, fish, poultry, red and organ meats, processed meats, added sugars, high-fat dairy products, low-fat dairy products, coffee and tea, nuts, other fats, refined grains, starchy vegetables and the supplement score. Dietary components were treated as continuous variables (g/d), standardised by sex to a mean of 0 and a standard deviation of 1·0, multiplied by the weight (β coefficient) and then summed (online Supplementary Table 1). The supplement score was calculated based on the consumption of supplemental vitamins A, E, D and C, β-carotene, thiamine, riboflavin, niacin, B6, B12, folate, Zn, Ca, Mg and Se as anti-inflammatory micronutrients and Fe as pro-inflammatory micronutrients. We ranked all vitamin and mineral supplement intakes into quantiles, assigning a value of 0 (low or no intake), 1 or 2 (highest intake) for anti-inflammatory micronutrients and 0 (low intake), –1 or –2 (highest intake) for pro-inflammatory micronutrients, and the values were then summed.
Four lifestyle components related to inflammation were included in the LIS, including obesity as assessed by BMI (kg/m2) (overweight (25–29·99) or obese (≥ 30)), cigarette smoking (former/never or current), physical activity as MET-h/d tertiles (low (< 34·3), moderate (34·3–37·7) and high (> 37·7)) and alcohol consumption (heavy (> 7 drinks/week), moderate (> 0 to ≤ 7 drinks/week) or none). Iranian people generally do not consume or report drinking because of religious beliefs and legal restrictions; therefore, we ignored alcohol consumption when calculating LIS. In order to calculate the LIS, dummy variables were created, coded ‘0’ for referent categories and ‘1’ for non-referent categories, multiplied by their assigned weights (online Supplementary Table 1) and summed. The weights of LIS components were based on the strength of their multivariate association with a panel of circulating inflammation-related biomarkers, such as IL-6, IL-8, IL-10 and C-reactive protein(Reference Byrd, Judd and Flanders7). We summed the DIS and LIS to calculate the DLIS. A high DIS, LIS and DLIS score (more positive) indicates a more inflammatory diet and lifestyle, while a low DIS, LIS and DLIS score (more negative) indicates the opposite.
Statistical analysis
Descriptive statistics were presented for each participant’s characteristics, including numbers (percentages) for categorical variables and mean values and standard deviations for continuous variables. A χ 2 test (or Fisher’s exact test) was used for categorical variables, while a two-independent samples t test (or Mann–Whitney test) was used for continuous variables. OR and 95 % CI were calculated using multivariate unconditional logistic regression models to estimate the association of DIS, LIS and DLIS tertiles with T2DM. Tertiles were calculated according to the distributions of the participants without T2DM. We considered the first tertiles as reference groups. For all final models, LIS and DLIS adjusted for potential confounders including age (years), sex (male/female), educational level (≤ high school/> high school), marital status (single/married), job status (jobless/have a job) and total energy intake (kcal/d). In the DIS models, we also included BMI (kg/m2), current smoking status (yes/no) and physical activity (MET-h/d). In order to assess the potential interaction between DIS and LIS, a joint/combined (cross-classification) multivariable logistic regression analysis was conducted in which the reference group includes participants in the first tertile of both scores. Additionally, univariate linear regression models were used to assess the association between cardiometabolic risk factors and DLIS.
All statistical analyses were done using SPSS statistical software, version 22 (IBM SPSS Statistics for Windows, version 22.0, IBM Corp.). A P-value less than 0·05 or a 95 % CI for OR that excluded 1·0 is considered statistically significant.
Result
Participants in the study were 35–70 years old, with a mean age of 48·29 (sd 8·53) (individuals without T2DM: 47·66 (sd 8·42); individuals with T2DM: 50·44 (sd 8·57)). Table 1 presents the baseline characteristics of the participants. As compared with individuals without T2DM, patients with T2DM were significantly older and had lower academic education levels, serum concentrations of HDL-cholesterol, LDL-cholesterol, aspartate aminotransferase, and higher BMI, WC, WHR, SBP, DBP, serum concentrations of fasting blood sugar, TAG, total cholesterol, alanine aminotransferase, alkaline phosphatase and γ-glutamyl transferase.
Table 1. Baseline characteristics of participants with and without T2DM in the SPCS (n 2732)*
(Numbers and percentages; mean values and standard deviations)
ALP, alkaline phosphatase; AST, aspartate aminotransferase; DBP, diastolic blood pressure; FBS, fasting blood sugar; GGT, γ-glutamyl transferase; MET, metabolic equivalent task; SBP, systolic blood pressure; SPCS, Sabzevar Persian Cohort Study; T2DM, type 2 diabetes mellitus; WC, waist circumference; WHR, waist-to-hip ratio; ALT, alanine aminotransferase.
* Values are means ± sd unless otherwise indicated. P values were computed by Student t test for continuous variables and χ 2 test for categorical variables.
† Never married, widowed or divorced.
Table 2 shows the components of DIS and LIS among participants with and without T2DM. In comparison with non-T2DM patients, T2DM patients had a significantly higher DIS and consumed more energy, carbohydrates, fats, red and organ meats, other fats, refined grains and starchy vegetables. There was no significant difference between the two groups in terms of the LIS and its components. However, patients with T2DM had significantly higher DLIS than individuals without T2DM.
Table 2. DIS and LIS components of participants with and without T2DM in the SPCS (n 2732)*
(Mean values and standard deviations; numbers and percentages)
DIS, dietary inflammation score; DLIS, dietary and lifestyle inflammation score; LIS, lifestyle inflammation score; T2DM, type 2 diabetes mellitus; SPCS, Sabzevar Persian Cohort Study.
* Values are means ± sd unless otherwise indicated. P values were computed by Student t test for continuous variables and χ 2 test for categorical variables.
† According to the text and online Supplementary Table 1, the DIS is composed of nineteen weighted components; a higher score indicates a more pro-inflammatory diet.
‡ According to the original report, the LIS was based on four weighted components (BMI, smoking, physical activity and alcohol intake). However, the present study excluded current alcohol consumption, so we calculated a LIS based solely on BMI, smoking and physical activity, as described in the text and online Supplementary Table 1; a higher score represents a more pro-inflammatory lifestyle.
§ The DLIS is calculated by summing the DIS and LIS.
The association of crude and multivariable-adjusted DIS, LIS and DLIS with the risk of T2DM is shown in Table 3. Multivariate adjustment strengthened the positive associations between higher DIS and LIS with T2DM risk. In the fully adjusted multivariable models, among those in the highest relative to the lowest DIS and DLIS tertile, the odds of T2DM were statistically nearly 3·5-fold (OR: 3·41; 95 % CI 2·66, 4·38; P trend < 0·001 and OR: 3·40; 95 % CI 2·65, 4·35; P trend < 0·0001, respectively). Among those in the highest relative to the lowest LIS tertile, the odds of T2DM were not significant (P trend = 0·521).
Table 3. Associations of the DIS and the LIS with T2DM in the SPCS study (n 2732)*
(Odds ratios and 95 % confidence intervals)
DIS, dietary inflammation score; DLIS, dietary and lifestyle inflammation score; LIS, lifestyle inflammation score; SPCS, Sabzevar Persian Cohort Study; T2DM, type 2 diabetes mellitus.
* Values are OR (95 % CI) from multivariate unconditional logistic regression unless otherwise indicated.
† Unadjusted.
‡ Adjusted for age (years, continuous), sex and total energy intake (kcal/d, continuous).
§ Adjusted for age (years, continuous), sex, educational level (≤ high school/> high school), marital status, job status (jobless/have a job), total energy intake (kcal/d, continuous), BMI, currently smoke (yes/no) and physical activity level (MET-h/d, continuous).
|| Adjusted for age (years, continuous), sex, educational level (≤ high school/> high school), marital status, job status (jobless/have a job) and total energy intake (kcal/d, continuous).
Table 4 shows the joint and combined (cross-classification) associations of the DIS and LIS with T2DM among all participants combined. As a result of the fully adjusted model, relative to those in the lowest joint DIS/LIS tertile, among those in the lowest DIS tertile, T2DM risk was higher with a higher LIS. In addition, among those in the lowest LIS tertile, the risk was higher among those with a higher DIS. However, the greatest risk of T2DM was among those in the highest joint DIS/LIS tertile (OR: 3·37; 95 % CI 2·13, 5·32; P interaction < 0·001).
Table 4. Joint/combined associations of the DIS and LIS with T2DM in the SPCS study (n 2732)*
(Odds ratios and 95 % confidence intervals)
DIS, dietary inflammation score; DLIS, dietary and lifestyle inflammation score; LIS, lifestyle inflammation score; SPCS, Sabzevar Persian Cohort Study; T, tertile; T2DM, type 2 diabetes mellitus.
* Values are OR (95 % CI) from multivariable logistic regression analysis unless otherwise indicated.
† Unadjusted.
‡ Adjusted for age (years, continuous), sex and total energy intake (kcal/d, continuous).
§ Adjusted for age (years, continuous), sex, educational level (≤ high school/> high school), marital status, job status (jobless/have a job) and total energy intake (kcal/d, continuous).
Table 5 shows that WC (P < 0·001) and WHR (P = 0·010) were significantly associated with higher DLIS in both participants with and without T2DM, but these correlations were higher in patients with T2DM.
Table 5. DLIS relation with anthropometric measurements and blood biomarker concentrations*
(β-coefficients and 95 % confidence intervals)
ALT, alanine aminotransferase; ALP, alkaline phosphatase; AST, aspartate aminotransferase; DBP, diastolic blood pressure; DLIS, dietary and lifestyle inflammation score; FBS, fasting blood sugar; GGT, γ-glutamyl transferase; MET, metabolic equivalent task; SBP, systolic blood pressure; SPCS, Sabzevar Persian Cohort Study; T2DM, type 2 diabetes mellitus; WC, waist circumference; WHR, waist-to-hip ratio.
* Values are β and 95 % CI for β from univariate linear regression models unless otherwise indicated.
† Unadjusted.
‡ Adjusted for age (years, continuous), sex and total energy intake (kcal/d, continuous).
§ Adjusted for age (years, continuous), sex, educational level (≤ high school/> high school), marital status, job status (jobless/have a job) and total energy intake (kcal/d, continuous).
Discussion
The current study found a positive association between DIS and DLIS with increasing odds of T2DM. In addition, there was a significant positive association between DLIS and WC and WHR; however, no significant association was found between DLIS and other components of cardiometabolic risk factors.
Various dietary scores have been developed to evaluate the impact of dietary ingredients on inflammation, such as empirical dietary inflammatory pattern (EDIP) score(Reference Tabung, Smith-Warner and Chavarro18) and dietary inflammation index (DII)(Reference Shivappa, Steck and Hurley19). According to the two recent prospective studies, a high EDIP score was associated with an increased risk of T2DM(Reference Jin, Shi and Aroke20,Reference Lee, Li and Li21) . Two cross-sectional studies conducted in Iran suggest that a higher EDIP score could increase the risk of diabetes(Reference Shakeri, Mirmiran and Khalili-Moghadam22,Reference Soltani, Moslehi and Hosseini-Esfahani23) . Moreover, several studies have found a significant association between metabolic disorders and DII, which represents the dietary inflammatory potential(Reference Kim, Lee and Kim24,Reference Nikniaz, Nikniaz and Shivappa25) . The DII is largely nutrient based rather than food based, which may not fully account for all the dietary components that can affect inflammation individually and collectively(Reference Shivappa, Steck and Hurley19). In addition, although the EDIP is a whole foods-based score, it is primarily based on data from Nurses’ Health Study participants with relatively homogeneous occupational and demographic characteristics, which may limit its generalisability or applicability(Reference Tabung, Smith-Warner and Chavarro18). Additionally, other lifestyle factors, such as physical inactivity, obesity, tobacco use and alcohol consumption, have not been considered in either EDIP or DII. Weighted DIS and LIS inflammation biomarker panels were developed to address the limitations of DII and EDIP and characterise the collective effects of whole foods, beverages, supplements and lifestyle on inflammation. Byrd et al.(Reference Byrd, Bostick and Judd10) found that the DIS was more strongly associated with biomarkers of inflammation than the DII and EDIP. Moreover, the LIS showed a stronger association with biomarkers than any of the LIS, and the strongest association was among those in the joint highest DIS and LIS categories. Subsequently, the highest concentrations of circulating inflammation biomarkers were found in participants with a high DIS combined with a high LIS, rather than those with a low DIS combined with a low LIS(Reference Byrd, Judd and Flanders7).
Recently, a prospective cohort among participants in the Tehran Lipid and Glucose Study found a strong positive association between LIS and EDIP, and the risk of T2DM, but not with DIS scores(Reference Teymoori, Farhadnejad and Mokhtari11). Furthermore, other studies have examined the association between DIS and LIS and the risk of various chronic disorders, including the metabolic syndrome(Reference Dehghani Firouzabadi, Jayedi and Asgari26) and metabolic associated fatty liver disease(Reference Taheri, Bostick and Hatami27). In a nested case–control study, Taheri et al.(Reference Taheri, Bostick and Hatami27) showed that higher adherence to the inflammatory potential of diet and lifestyle was associated with a risk of metabolic associated fatty liver disease. Also, according to Dehghani Firouzabadi et al.(Reference Dehghani Firouzabadi, Jayedi and Asgari26), pro-inflammatory diets and lifestyles are associated with the metabolic syndrome and its components, such as abdominal obesity, and the risk of hypertension. In two prospective studies, Byrd et al. found an association between high DIS and LIS scores and an increased risk of all-cause, cancer- and CVD-specific mortality(Reference Byrd, Holmes and Judd28) as well as colorectal cancer(Reference Byrd, Bostick and Judd10). There is consistent evidence that chronically high levels of systemic inflammation contribute to the initiation and progression of several chronic diseases. According to epidemiological studies, circulating inflammatory biomarkers were directly associated with heart disease(Reference Schnabel, Yin and Larson29–Reference Ridker, Buring and Shih32), T2DM(Reference Hu, Meigs and Li33,Reference Pradhan, Manson and Rifai34) and hypertension risks(Reference Bautista, López-Jaramillo and Vera35). A comprehensive literature review found several dietary and lifestyle components may contribute to chronic inflammation(Reference Byrd, Judd and Flanders7). It is believed that the majority of plant foods, including vegetables, fruits, grains and nuts, have antioxidant and anti-inflammatory properties, while sugar, refined starches and trans and saturated fatty acids have pro-oxidants and pro-inflammatory properties(Reference Giugliano, Ceriello and Esposito36). In addition, it is possible that inflammation is particularly affected by exposures associated with certain lifestyles.
In this study, as opposed to the DIS and DLIS indices, the LIS was not associated with the risk of T2DM. However, there is a statistically significant interaction between LIS and DIS in relation to the risk of T2DM. In other words, individuals with both a high DIS and a high LIS had a higher risk of developing T2DM than those with both a low DIS and a low LIS. As a result of these findings, it is possible that lifestyle and diet may contribute to inflammation synergistically, and their simultaneous modification may reduce the risk of T2DM and possibly other metabolic diseases. According to another study, lifestyle-related inflammation, which addresses the cooperative effects of lifestyle-related factors, including BMI, physical activity and smoking, was associated with T2DM and the metabolic syndrome(Reference Dehghani Firouzabadi, Jayedi and Asgari26,Reference Taheri, Bostick and Hatami27) . Increasing BMI is positively associated with β-cell dysfunction, insulin resistance and high level of inflammatory markers(Reference Mtintsilana, Micklesfield and Chorell37,Reference Okura, Nakamura and Fujioka38) . Moreover, smoking can also be regarded as an independent risk factor for T2DM due to its detrimental effect on β-cells function, which causes insulin resistance, the release of cytokines and the up-regulation of inflammatory biomarkers(Reference Stadler, Tomann and Storka39). Another component of LIS is physical activity, which decreases the release of pro-inflammatory cytokines, enhances plasma antioxidant capacity, reduces chronic inflammation, decreases body fat mass by a negative energy balance and improves glucose and lipid metabolism(Reference Gomez-Cabrera, Domenech and Viña40).
According to the results of assessing cardiometabolic factors, followed diets and lifestyles with high inflammatory potential were positively associated with increased WC and WHR. Other cardiometabolic risk factors, including blood pressure, liver enzymes and glycaemic and lipid profiles, were not significantly associated with DLIS. The results of our study are consistent with two cross-sectional studies investigating the association between pro-inflammatory diets and lifestyles and components of the metabolic syndrome(Reference Dehghani Firouzabadi, Jayedi and Asgari26,Reference Muhammad, van Baak and Mariman41) . There has been evidence that pro-inflammatory diets and lifestyles are significantly associated with central obesity and WC(Reference Garralda-Del-Villar, Carlos-Chillerón and Diaz-Gutierrez42–Reference Farhangi and Vajdi44). Contrary to our findings, Abdurahman et al. (Reference Abdurahman, Bule and Azadbakhat45) found no significant association between a pro-inflammatory diet and an increase in WC. The study design, sample size variations, different lifestyles, diet parameters and dietary assessment tools have resulted in varying findings. Due to conflicting results, more research is needed to determine the association between LIS and DIS and cardiometabolic risk factors.
There were several strengths of this study, including its relatively large sample size, population-based design, comprehensive dietary and lifestyle exposures and medical history collection. In addition, previously validated FFQ and physical activity assessments of Iranians were used and filled out by expert interviewers during face-to-face interviews. Furthermore, this is the first study to investigate the relationship between DIS and LIS with T2DM and cardiometabolic risk factors, separately and jointly in a less industrialised area. This study has some potential limitations. First, measurement error due to self-reported dietary intake and other lifestyle factors was inevitable. The second limitation is that only baseline data were used in this study, meaning it is difficult to determine whether specific modifiable exposures or T2DM came first. Third, the weights assigned to DIS and LIS were validated for the US population and may not be suitable for other populations. Fourth, in our study, LIS did not include alcohol consumption. Fifth, although it would be better to validate DIS and LIS with inflammatory markers, unfortunately, no inflammatory parameters were available from the Sabzevar cohort data. Finally, as our study population was restricted to the Sabzevar city of Iran, generalisations to other populations may be limited.
In conclusion, in this study, there was a significant association between higher DIS and DLIS scores and a higher risk of T2DM in adults; however, LIS scores had no significant association with diabetes risk, although we found that interaction between LIS and DIS might increase the risk of T2DM. Dietary and lifestyle factors likely contribute to T2DM risk through inflammation, with dietary exposure contributing most significantly. However, lifestyle factors may also play an important role via other mechanisms. A more complete understanding of the role of diet, lifestyle and their combination in the development of T2DM as well as its potential mechanisms is needed through further epidemiological research.
Acknowledgements
Data from the enrolment phase of the Sabzevar Persian Cohort have been used in this study. We express appreciation to the participants in this study and to the staff of the Sabzevar Persian Cohort for their valuable help.
No specific funding was received from any agency in the public, commercial or not-for-profit sectors.
The authors’ responsibilities were as follows: F. B. and F. G.: conceived and designed the study; E. M.: analysed data or performed statistical analyses; F. B.: wrote the manuscript; S. J. and F. G.: critically revised the manuscript for important intellectual content and F. G.: had primary responsibility. All authors read and approved the final manuscript.
None of the authors declared a conflict of interest.
Supplementary material
For supplementary material referred to in this article, please visit https://doi.org/10.1017/S0007114523001903
