ABSTRACT
Background and Aims
Lifestyle and diet influence chronic disease risk through their impact on systemic inflammation. This research evaluated the association among dietary habits, physical activity, and inflammatory biomarkers, specifically glucose and C‐reactive protein (CRP).
Methods
This cross‐sectional study examined lifestyle, sociodemographic, and nutritional indicators using a structured questionnaire, which was adapted from the WHO STEPwise guideline. A total of 200 participants were included based on their attendance for CRP and glucose assays at two health centers between May and September 2023 in Bangladesh.
Results
Among participants with high fiber intake (> 20 g/day), 22% had normal blood glucose levels and 25.5% showed slightly increased CRP values. In contrast, among those with low fiber intake (< 10 g/day), 28% had pre‐diabetes, 23.5% had diabetes, and a moderate 56% exhibited moderately increased CRP levels. Besides, participants with higher saturated fat intake (> 10 g/day) showed moderate CRP elevations in 50%, pre‐diabetes in 24%, and diabetes in 19.5%, whereas those with lower intake (< 10 g/day) exhibited smaller CRP elevations in 28.5% and normal blood sugar levels in 27.5% of the group. Participants with a habit of rare or once‐weekly physical activity had pre‐diabetes in 38.5%, diabetes in 27%, and moderate CRP elevations in 57% of their group. On the contrary, those reporting regular physical activity demonstrated lower CRP levels in 20.5% and normal sugar levels in 34.5% of their group. Intake of fruit, vegetables, red meat, seafood, sugary drinks, high‐sugar foods, and smoking showed statistically significant associations with inflammatory biomarkers (p < 0.05); however, water intake did not exhibit a similar association. Glucose and CRP levels were found to be significantly associated with age, dietary factors (fiber, saturated fat, red meat, sugary diet), and lifestyle behaviors (physical activity, smoking), whereas sociodemographic factors (gender and education) showed no statistically significant associations.
Conclusion
The findings highlight associations between diet and physical activity and inflammatory markers, suggesting the necessity for focused public health interventions.
Keywords: behavioral factors, CRP, CVD, dietary practices, glucose
1. Introduction
A healthy lifestyle has been linked in multiple epidemiological studies to longer life expectancies and lower rates of death from various chronic illnesses [1]. Lifestyle factors such as sleep, physical activity, and exercise have a strong influence on biomarker levels. Moreover, dietary habits such as eating saturated fat, red meat, high sugar diets, fiber, etc., also play a great role in biomarkers [2]. Body mass index (BMI) also exerts a significant influence on regulating biomarker concentrations. Obesity, a major public health issue, is commonly measured by BMI, a marker strongly interrelated with inflammatory processes [3, 4]. C‐reactive protein (CRP) is a sensitive marker of inflammation that serves as an indicator to identify several diseases, such as cardiovascular disease (CVD) and coronary heart disease (CHD). CHD ranks as the highest cause of death among all CVDs, accounting for more than 8.9 million deaths worldwide [5]. The prevalence of CHD is increasingly unequal in different regions of the world, due to inadequate and a lack of better health services. CHD is considered a single cause of mortality and morbidity across all gender groups in developed and developing countries [6]. Saturated fat, fiber, BMI, smoking, red meat, etc., are considered nongenetic risk factors for CHD [7]. Fasting glucose is also an important marker that aids in identifying diabetes. Type 2 diabetes results from a combination of genetic, environmental, and behavioral risk factors. Moreover, although several genes associated with Type 2 diabetes have been identified, the genetic basis has not been fully elucidated, but there is strong evidence that such modifiable risk factors as obesity and physical inactivity are the main nongenetic determinants of the disease [8, 9, 10].
Many studies have focused on the effects of dietary patterns on CRP, an inflammatory marker. A healthy diet characterized by a high proportion of fruits, vegetables, whole grains, and unsaturated fatty acids has been shown to reduce inflammatory CRP in cross‐sectional studies [11, 12]. Similarly, low‐carbohydrate or low‐glycemic‐load diets have been shown to reduce inflammation and CVD risk factors [13].
Therefore, this cross‐sectional study aimed to observe associations between dietary/lifestyle factors and CRP and glucose.
2. Methods
2.1. Study Setting
The Japan Bangladesh Hospital (JBH) and Lab House Diagnostic Center (LDC) in the Chittagong division were the sites of the study. JBH has the capacity to accommodate 500–1000 patients daily. LDC is also capable of doing several pathological tests.
2.2. Study Design, Sample Size, and Sampling Method
This was a cross‐sectional hospital‐based study to determine the prevalence of lifestyle and dietary risk factors with inflammatory biomarkers CRP and glucose at JBH and LDC referral hospital. Information on participants' CVD status was not collected as it was beyond the scope of this study. The study was conducted between May and September 2023. The purposeful sampling method was employed to select 200 patients who met the study selection criteria following a prior study conducted in Bangladesh for inflammatory biomarkers [14]. This prior study informed sample size determination; the participants of the current study were independent from that cohort. The questionnaire was administered face‐to‐face by trained interviewers.
2.3. Inclusion and Exclusion Criteria
2.3.1. Inclusion Criteria
Adults aged ≥ 20 years who attended to assay the level of CRP and glucose at JBH and LDC referral hospital from May to September 2023. The glucose level is measured during the fasting period. The study participants voluntarily consented to participate in the study.
2.3.2. Exclusion Criteria
Children (including congenital heart disease), pregnant women, and adults who did not consent were excluded from the study.
2.4. Assessment of Sociodemographic Characteristics and Lifestyle Risk Factors
A structured questionnaire with closed questions was adopted from the WHO STEPwise survey and translated into the Bengali language (national language) [15, 16]. The questionnaire was then administered to all participants. The following information was collected: sociodemographic information, lifestyle, and dietary risk factors. The assessed sociodemographic characteristics were: age, gender, and education level. Education level was categorized as below secondary, secondary, and higher secondary, and higher education. Lifestyle risk factors included current/history of smoking (categorized as smoker or non‐smoker), history of alcohol use (categorized as current alcohol user or non‐alcoholic user), physical activity (categorized as physical exercise at least once per week minimum for 30 min or no physical activity), dietary habits included saturated fat (categorized by ≥ 7 gm/day to < 13 gm/day), dietary fiber intake from food sources (categorized by ≤ 10 gm/day to > 25 gm/day), sugary drinks (categorized by at least once a week). Former smokers were categorized as smokers due to the possible lingering impact on biomarkers. Here, lifestyle and dietary risk factors have been adapted from the WHO STEPwise survey guideline for non‐communicable diseases [16]. Nutritional information was obtained via self‐report of average daily intake by the respondents. Moreover, cut‐offs for saturated fat and fiber consumption were based on WHO dietary recommendations [17].
2.5. Anthropometric Measurements
Weight in kilograms was taken in light clothing by using a calibrated weighing scale machine (Seca, Germany), with a 150 kg capacity and an accuracy of 0.5 kg. Height was measured in centimeters (cm) by a calibrated stadiometer (Leicester stadiometer) of 0.1 cm accuracy, with the subject standing against the vertical wall, heels together, shoulders and head touching the wall surface, and after removal of shoes. BMI was then calculated by the following formula [BMI = weight (kg)/height (m2)]. BMI was categorized as underweight (< 18.5), normal (18.5–24.9), overweight (25.0–29.9), and obese (≥ 30.0) [18].
2.6. Blood Sample Collection
Blood samples for plasma glucose and serum CRP concentration measurements were obtained by a trained clinician. For each patient, 10 mL of venous blood samples were drawn from the arm and transferred to an ethylenediaminetetraacetic acid tube. Blood samples were then taken to a clinical research laboratory at JBH and the LDC referral hospital for further analysis procedures. Blood samples were centrifuged at approximately 1500 g for 5 min at 4°C. Clarified serum and plasma samples were then pipetted and poured into Eppendorf storage tubes (5 mL), followed by freezing at −20°C. Glucose was measured in plasma; CRP was measured in serum (mg/L).
2.7. Analysis of Biomarkers
Before analysis, plasma and serum blood samples were mixed thoroughly by using a vortex mixer. From each sample, 10 μL was pipetted and poured into Microvette tubes. Plasma blood glucose samples were loaded into the Cobas Integra 400 plus analyzer (Roche Diagnostics, Germany). Serum blood for measuring CRP concentration was loaded into a fully‐auto chemiluminescence immunoassay analyzer (MAGLUMI 800), Shenzhen New Industries Biomedical Engineering Co. Ltd. (Snibe Diagnostic, China). According to laboratory protocols, values (concentrations) of studied biochemistry markers were categorized as indicated in Table 1.
Table 1.
Classification of biochemical markers.
| Biomarker | Descriptors |
|---|---|
| Fasting blood glucose (mg/dL) | |
| 70–100 | Normal |
| 100–125 | Pre‐diabetes |
| > 126 | Diabetes |
| CRP (mg/L) | |
| < 1 | Normal |
| 1–3 | Moderate risk |
| > 3 | High risk |
Note: For CRP, minor elevation: 1–3 mg/L; moderate elevation: > 3 mg/L (WHO criteria).
2.8. Ethical Consideration
The Noakhali Science and Technology University Ethical Committee provided ethical permission for this study (Study ID: NSTU/SCJ/EC/2023/44). Informed consent has been collected from each participant before collecting quantitative data, settled by questionnaire, and also for collecting biomarker data.
2.9. Statistical Analysis
Data were entered into Microsoft Excel 2021, then sorted, coded, and cleaned. The analysis was done using SPSS version 26 (IBM). Descriptive statistics were used to analyze the frequency and percentages of sociodemographics, lifestyle characteristics, and biomarkers, like CRP and glucose. Pearson's chi‐square (χ2) test was used to determine the association between risk factors and CRP and glucose. The main outcome variables were categorized following WHO guideline cutoffs to maintain comparability with previous data. Independent variables included in the analysis were gender, age, education level, BMI, physical activity, smoking history, and alcohol consumption. Independent variables significantly associated with plasma blood sugar and CRP levels in the chi‐square (χ2) test were subjected to a multinomial logistic regression model to estimate unadjusted odds ratios (ORs) with 95% confidence intervals (CIs) for associations between sociodemographic, dietary, and lifestyle factors and glucose or CRP categories. Adjusted multinomial logistic regression models were assessed; however, due to model instability and non‐convergence, adjusted results were unreliable, and therefore, the outcome was omitted. Only unadjusted ORs are reported, which remained stable and interpretable. The adjusted multinomial logistic regression model comprised the following covariates based on theoretical importance and STROBE recommendations: age, gender, education level, BMI, smoking status, alcohol use, physical activity, dietary fiber intake, saturated fat intake, sugary drink intake, red meat consumption, and high‐sugar diet.
3. Results
3.1. Characteristics of the Study Population
Among the 200 patients recruited in the study, 49% were men and 51% were women, respectively. The majority were aged 51–60 years (45.5%), followed by 41–50 years (22%), 20–30 years (21.5%), and 31–40 years (11%). In terms of weight, most respondents (66%) weighed 51–70 kg, and only 5% were between 30 and 50 kg. Regarding educational status, 44.5% had higher education, while 43% had education below the secondary level (Table 2).
Table 2.
Characteristic of the study population (N = 200).
| Characteristic | Sub‐category | n (%) |
|---|---|---|
| Gender | Female | 102 (51) |
| Male | 98 (49) | |
| Age (year) | 20–30 | 43 (21.5) |
| 31–40 | 22 (11) | |
| 41–50 | 44 (22) | |
| 51–60 | 91 (45.5) | |
| Weight (kg) | 30–50 | 10 (5) |
| 51–70 | 132 (66) | |
| 71–90 | 58 (29) | |
| Educational qualification | Below secondary | 86 (43) |
| Secondary and higher secondary | 25 (12.5) | |
| Higher education | 89 (44.5) |
3.2. Association Between CRP and Glucose Level With Demographic Factors
Gender was not significantly associated with either glucose (p = 0.444) or CRP level (p = 0.153). However, only age showed a statistically significant association with both glucose (p = 0.006) and CRP levels (p < 0.001), indicating that older age groups were more likely to have diabetes or pre‐diabetes and elevated CRP values. No statistically significant associations were observed between body weight and either glucose (p = 0.971) or CRP level (p = 0.069). Similarly, education level was also not significantly related to glucose (p = 0.090) or CRP levels (p = 0.679) (Table S1).
3.3. Proportion and Association of Lifestyles and Dietary Factors With Blood Glucose
The proportion of glucose for lifestyles and dietary habits was assessed for each participant involved in the study, and the results are summarized in Table S2. People who consumed more fiber had a higher proportion of normal blood glucose levels. Among the 200 participants, 31 consumed more than 25 g/day of dietary fiber; of these, 0.5% were diabetic, 3.5% were pre‐diabetic, and 11.5% had normal glycemic status. Conversely, people who consumed equal to or less than 10 gm/day of fiber had higher blood glucose levels. Of the 200 participants, 116 had a daily dietary fiber intake of less than 10 g, but only 6.5% of participants had normal blood glucose conditions; others, that is, 28% and 23.5%, were pre‐diabetic and diabetic conditions. Similarly, participants with high sugar intake, smoking habits, excess body weight, or low physical activity levels were more likely to have pre‐diabetic or diabetic conditions, with all factors demonstrating statistically significant associations (p < 0.05).
3.4. Proportion and Association of Lifestyles and Dietary Factors With Blood CRP
The proportion of CRP for lifestyles and dietary habits was assessed for each participant involved in the study, and the results are summarized in Table S3. In the study, people who consumed more saturated fat, red meat, and smoked meat had elevated CRP levels were elevated. For example, 59 people from 200 participants had equal or less than 7 g/day saturated fat, only 4% had high CRP levels, others (25.5%) had CRP levels that were minor elevated. In contrast, fibers and seafood are associated with the CRP level. Each factor showed a statistically significant association with CRP (p < 0.001).
3.5. Associations Between Lifestyle and Dietary Factors and Glucose Categories
Table 3 depicts that glucose levels were significantly associated with age, dietary fiber intake, saturated fat intake, red meat consumption, sugary drink intake, high‐sugar diet, and smoking status (p < 0.05). Specifically, younger age groups (20–30 and 31–40 years), low fiber intake (≤ 10 g/day), lower saturated fat intake (≤ 10 g/day), frequent red meat consumption, sugary drink intake, absence of a high‐sugar diet, and non‐smoking status demonstrated statistically significant associations. On the contrary, gender, educational qualification, and drinking water intake were not significantly associated with glucose level categories (p > 0.05).
Table 3.
Associations between lifestyle and dietary factors and glucose level categories based on multinomial logistic regression.
| Factors | Sub‐categories | Unadjusted OR (95% CI) | p value |
|---|---|---|---|
| Gender | Female | 1.451 (0.807–2.606) | 0.213 |
| Male | Ref | ||
| Age | 20–30 | 0.245 (0.113–0.533) | 0.000 |
| 31–40 | 0.282 (0.107–0.745) | 0.011 | |
| 41–50 | 0.545 (0.246–1.208) | 0.135 | |
| 51–60 | Ref | ||
| Education | Below secondary | 0.996 (0.537–1.847) | 0.990 |
| Secondary and higher secondary | 1.778 (0.644–4.905) | 0.266 | |
| Higher education | Ref | ||
| Dietary fiber intake (g/day) | ≤ 10 | 22.779 (8.465–61.300) | 0.000 |
| > 10 but ≤ 20 | 2.396 (0.749–7.662) | 0.141 | |
| > 20 but ≤ 25 | 1.369 (0.455–4.121) | 0.576 | |
| > 25 | Ref | ||
| Saturated fat intake (g/day) | ≤ 7 | 0.058 (0.018–0.186) | 0.000 |
| > 7 but ≤ 10 | 0.202 (0.060–0.684) | 0.010 | |
| > 10 but ≤ 13 | 0.655 (0.190–2.257) | 0.502 | |
| > 13 | Ref | ||
| Red meat (beef, pork) intake | Never | 0.088 (0.007–1.035) | 0.053 |
| Rarely | 0.090 (0.027–0.300) | 0.000 | |
| Once a week | 0.329 (0.064–1.701) | 0.185 | |
| Several times a week | 1.000 (0.340‐2.942) | 1 | |
| Everyday | Ref | ||
| Sugary drinks (soda, sweetened teas) intake | Never | 9.333 (0.911–95.571) | 0.060 |
| Rarely | 17.429 (1.806–168.189) | 0.013 | |
| Once a week | 4.944 (0.526–46.887) | 0.162 | |
| Several times a week | 3.692 (0.360–37.856) | 0.271 | |
| Everyday | Ref | ||
| Drinking water (mL) | Less than 500 | 0.695 (0.111–4.334) | 0.695 |
| 500–1000 | 0.735 (0.402–1.344) | 0.317 | |
| 1000–2000 | Ref | ||
| High‐sugar diet (candy, sugary drinks) | No | 0.009 (0.003–0.024) | 0.000 |
| Yes | Ref | ||
| Smoking | No | 0.270 (0.146–0.498) | 0.000 |
| Yes | Ref |
Note: Here, the associations between lifestyle and dietary factors and glucose level categories are significant at a p value of < 0.05.
3.6. Associations Between Lifestyle and Dietary Factors and CRP Categories
Table 4 demonstrates that CRP level categories were significantly associated with age, dietary fiber intake, high‐sugar diet, physical activity, and smoking status (p < 0.05). Specifically, younger adults (20–40 years) had significantly lower odds of elevated CRP compared with older age groups, while low fiber intake (≤ 25 g/day) was found to be strongly associated with higher CRP levels. In addition, patients reporting no high‐sugar diet, being involved in daily physical activity, and being non‐smokers demonstrated protective associations, whereas those with infrequent physical activity (rarely/never or once a week) had remarkably increased odds of elevated CRP. Conversely, this analysis found no statistically significant association between CRP levels and gender, education qualification, sugary drink intake, drinking water consumption, and BMI (p > 0.05).
Table 4.
Associations between lifestyle and dietary factors and CRP level categories based on multinomial logistic regression.
| Factors | Sub‐categories | Unadjusted OR (95% CI) | p value |
|---|---|---|---|
| Gender | Female | 1.564 (0.845–2.894) | 0.155 |
| Male | Ref | ||
| Age | 20–30 | 0.081 (0.034–0.197) | 0.000 |
| 31–40 | 0.115 (0.040–0.327) | 0.000 | |
| 41–50 | 0.619 (0.229–1.669) | 0.343 | |
| 51–60 | Ref | ||
| Education | Below secondary | 0.901 (0.466–1.743) | 0.757 |
| Secondary and higher secondary | 0.656 (0.256–1.683) | 0.381 | |
| Higher education | Ref | ||
| Dietary fiber intake (g/day) | ≤ 10 | 406.000 (70.848–2382.603) | 0.000 |
| > 10 but ≤ 20 | 91.833 (14.007–602.064) | 0.000 | |
| > 20 but ≤ 25 | 5.932 (1.163–30.254) | 0.032 | |
| > 25 | Ref | ||
| Sugary drinks (soda, sweetened teas) intake | Never | 1.333 (0.191–9.311) | 0.772 |
| Rarely | 2.275 (0.351–14.744) | 0.389 | |
| Once a week | 1.882 (0.289–12.247) | 0.508 | |
| Several times a week | 0.722 (0.102–5.095) | 0.744 | |
| Everyday | Ref | ||
| Drinking water (mL) | Less than 500 | 0.253 (0.040–1.582) | 0.142 |
| 500–1000 | 0.914 (0.483–1.730) | 0.782 | |
| 1000–2000 | Ref | ||
| High‐sugar diet (candy, sugary drinks) | No | 0.130 (0.066–0.258) | 0.000 |
| Yes | Ref | ||
| BMI | Normal | 0.220 (0.022–2.216) | 0.199 |
| Overweight | 2.821 (0.273–29.135) | 0.384 | |
| Obese | Ref | ||
| Physical activity | Rarely or never | 13.714 (4.687–40.127) | 0.000 |
| Once a week | 13.200 (4.940–35.275) | 0.000 | |
| Several times a week | 1.789 (0.675–4.748) | 0.242 | |
| Daily | Ref | ||
| Smoking | No | 0.072 (0.032–0.160) | 0.000 |
| Yes | Ref |
Note: Here, the associations between lifestyle and dietary factors and CRP level categories are significant at a p value of < 0.05.
4. Discussion
This study evaluated the association between lifestyle factors and inflammatory markers, with CRP as the main outcome and glucose as a secondary outcome variable. However, as participants in this study were recruited from hospital settings, they may represent individuals with poorer health conditions than the general population. This selection bias could overestimate associations between unhealthy behaviors of participants and elevated biomarkers.
4.1. Comparison of Findings Associated With Lifestyle Factors
This study showed that only 16.5% people engaged in physical exercise daily, and 18% people several times a week, respectively, in this region. Low levels of physical activity among patients have been related to aging, cardiovascular symptoms, and other chronic diseases, such as arthritis, which reduces walking ability [19]. In the present study, a large number of patients were overweight and obese, 38.5% and 25%, respectively. This has been related to the lower level of physical activity and glucose levels, characterized by low consumption of fruits and vegetables [20, 21, 22, 23, 24]. Moreover, in this study, 55.5% of participants were smokers, which was alarming in this region. Although no region‐specific data were found for current smoking prevalence in Bangladesh, the prevalence of smoking among adults aged 15 years and older was found to be 16.8% in 2022 [25]. Smoking is considered linked to increased heart‐related disease [26, 27, 28, 29].
4.2. Comparison of Findings Associated With Dietary Factors
Around 65% of participants described frequent intake of high‐sugar foods, reflecting a rising trend of high‐sugar consumption among patients with abnormal glucose levels [30, 31]. In addition, 18.5% of participants had a saturated fat intake exceeding 13 g/day. Saturated fats have long been associated with an increased risk of heart disease. They were believed to raise LDL cholesterol levels (often termed “bad” cholesterol). Furthermore, 12% people were found to consume red meat daily. High intake of red meat, particularly processed red meat (like bacon, sausages, and deli meats), may be associated with an increased risk of certain types of cancer, especially colorectal cancer. This association might be related to compounds formed during cooking or processing, such as heterocyclic amines or polycyclic aromatic hydrocarbons [32, 33, 34]. Dietary fibers are a crucial component of a healthy diet found in fruits, vegetables, whole grains, legumes, nuts, and seeds. In this study, 62% participants were found to take more than 20 g/day fiber, which may help to control the blood sugar and potentially may reduce the risk of Type 2 diabetes. Fiber, like soluble fiber found in oats, beans, and fruits, can help lower LDL cholesterol levels (the “bad” cholesterol), reducing the risk of heart disease [35, 36, 37]. In this study, about 45 participants were found to consume seafood. Seafood, especially fatty fish like salmon, mackerel, and sardines, is abundant in omega‐3 fatty acids, particularly eicosapentaenoic acid and docosahexaenoic acid [38]. These fatty acids are essential for brain health, reducing inflammation, and supporting heart health [39, 40, 41, 42, 43]. Results from this study also showed a statistically significant association between plasma glucose and CRP.
4.3. Strengths and Limitations of This Study
This study included primary data by visiting each study setting and directly observing the diagnosis reports in the selected centers. In addition, this study incorporated a few semi‐structured questions, adhering to the WHO STEPwise guidelines for data collection. However, the relatively small sample size was due to a budget shortage, and it was not possible to employ a more representative sampling method. However, despite these constraints, the obtained results from this study can still be used in the monitoring and evaluation of glucose and CRP biomarkers. Dietary intake information was reported based on the self‐response from the respondents, which may be subject to recall or reporting bias.
5. Conclusion
This study revealed associations between dietary and lifestyle factors with CRP and glucose levels. High fiber consumption and regular physical activity were found to be associated with favorable profiles, while high saturated fat intake, low activity, and smoking were associated with increased CRP and glucose. These findings indicate associations only; further longitudinal study is suggested to confirm causal relations.
Author Contributions
Mohammad Ariful Islam: Conceptualization, methodology, data curation, resources, writing – original draft, writing – review and editing; Reaz Morshed: conceptualization, methodology, resources, supervision, writing – review and editing; Shamim Alam: writing – original draft, writing – review and editing; Jakir Hossain: supervision, writing – review and editing; Md Shahedul Islam: data curation, visualization, formal analysis, resources, software, writing – original draft, writing – review and editing.
Funding
The authors received no specific funding for this work.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The lead author, Md Shahedul Islam, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Supporting information
Supplementary Table S1: Cross tabulation between glucose & CRP level and demographic factors (N = 200). Supplementary Table S2: Proportion and association of factors with blood glucose level (N = 200). Supplementary Table S3: Proportion and association of factors with blood CRP level (N = 200).
Acknowledgments
The authors would like to convey their gratitude to the Department of Biochemistry and Molecular Biology, Noakhali Science and Technology University, Bangladesh, and Japan‐Bangladesh Hospital, Noakhali, and Lab Housed Diagnostic Center, Cox's Bazar, for supporting this study.
Islam M. A., Morshed R., Alam S., Hossain J., and Islam M. S., “Association Between Lifestyle and Dietary Habits With C‐Reactive Protein and Glucose: A Cross‐Sectional Study,” Health Science Reports 9 (2026): 1‐8, 10.1002/hsr2.71741.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Table S1: Cross tabulation between glucose & CRP level and demographic factors (N = 200). Supplementary Table S2: Proportion and association of factors with blood glucose level (N = 200). Supplementary Table S3: Proportion and association of factors with blood CRP level (N = 200).
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.