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Abstract
Objective The aim of this study is to evaluate diet quality and other associated factors with dyslipidaemia in cardiovascular disease (CVD) patients in Bangladesh.
Design The study employed a cross-sectional design.
Setting Data from medical records, dietary intake and socioeconomic factors were collected from January to October 2022 at the National Institute of Cardiovascular Disease, Dhaka, and Noakhali Sadar Hospital.
Participants A total of 570 CVD patients, aged 25–80 years, with a confirmed diagnosis within the past 3 months, were included in the study.
Main outcome measures The primary outcomes were the Global Diet Quality Score (GDQS) and dyslipidaemia. Multivariate logistic regression models were used to explore the associations between dyslipidaemia and various sociodemographic, nutritional, and dietary factors in CVD patients.
Results Dyslipidaemia was identified in more than two-thirds (70.4%) of participants. The mean GDQS was 24.38, with 69.8% of the population maintaining a healthy diet. GDQS was significantly higher in the non-dyslipidaemic group (25.21±2.53) compared with the dyslipidaemic group (24.03±2.33). Nutrient intake was generally higher in non-dyslipidaemic patients. The odds of hypercholesterolaemia, hypertriglyceridaemia and elevated low-density lipoprotein (LDL) were notably higher for participants in the lowest GDQS tertile compared with the highest. Multivariable logistic regression identified sex, employment status, body mass index (BMI) and GDQS as significant predictors of dyslipidaemia. Males (adjusted odds ratio (AOR)=4.18, 95% CI 2.32 to 7.54), homemakers (AOR=2.86) and obese individuals (AOR=1.0) were at increased odds of dyslipidaemia. Compared with the highest GDQS tertile, the odds of dyslipidaemia were nearly double in the middle tertile (AOR: 1.87, 95% CI 1.13 to 3.11) and almost four times higher in the lowest tertile (AOR: 3.67, 95% CI 2.02 to 6.64).
Conclusions A high-quality diet was associated with significantly lower odds of dyslipidaemia, hypercholesterolaemia, hypertriglyceridaemia and elevated LDL cholesterol. The study findings highlight the potential of targeted nutritional interventions with a multifaceted approach to managing dyslipidaemia, emphasising the need for personalised dietary guidelines that consider the individual’s gender, occupation and BMI.
- Cardiovascular Disease
- Cross-Sectional Studies
- NUTRITION & DIETETICS
- PUBLIC HEALTH
Data availability statement
Data are available upon reasonable request. All data are available in the manuscript.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
The Global Diet Quality Score (GDQS), which combines 25 healthy and unhealthy food groups, is a sensitive metric for assessing diet quality.
The sample size was sufficient to allow for multivariate logistic regression models on nine independent variables, and the model demonstrated a good fit.
The cross-sectional design of this study prevents the establishment of causation between diet quality and dyslipidaemia, restricting the findings to associations only.
While adjustments were made for potential confounders, the possibility of residual confounding, such as the effects of lipid-lowering medications, cannot be entirely ruled out.
Introduction
Heart disease is increasing worldwide, with South Asian nations experiencing the greatest prevalence and mortality rates among all low and middle income countries (LMICs).1 South Asians are 3–5 times more likely to acquire heart disease, presenting symptoms 5–10 years earlier than in Western countries.1 Among these nations, Bangladesh, bears a disproportionate burden, with one of the highest incidences of cardiovascular disease (CVD) in the region, often affecting individuals at a younger age.2 This escalating epidemic poses a significant challenge to public health, as CVD remains a leading cause of morbidity and mortality in Bangladesh.3 The prevalence of CVD in the country varies widely, with estimates ranging from 0.062% to 77.7%, and pooled data suggest a 5% prevalence rate across the population, regardless of gender or geographical location.3
Several risk factors contribute to the increasing rates of CVD in Bangladesh, including hypertension, elevated total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, triglycerides (TG), reduced levels of high-density lipoprotein (HDL) cholesterol, obesity and poor dietary habits.4 Dyslipidaemia is widely recognised as a significant risk factor for CVD and associated mortality in countries with developed and developing economies.4 5 An increased prevalence of dyslipidaemia has been reported in Bangladesh.3 5 This indicates that dyslipidaemia may have a substantial impact on the emergence of CVD in Bangladesh.
Dyslipidaemia is characterised by abnormal lipids and lipoprotein levels in the blood, occurring either independently or in combination. In adult cardiac patients, dyslipidaemia can exacerbate pre-existing heart conditions and lead to further health complications. Atherosclerosis, caused by the accumulation of fatty deposits in the arteries, significantly elevates the risk of angina, myocardial infarction and stroke in individuals with dyslipidaemia.6 Elevated LDL cholesterol and triglyceride levels are particularly concerning, as they increase the risk of plaque rupture, thrombosis and life-threatening coronary artery blockages.7 Cardiac patients with dyslipidaemia are more vulnerable to recurrent heart attacks due to the heightened risk of plaque instability and thrombosis, which may further damage the heart muscle and impair cardiac function.8
Diet quality is closely linked to lipid metabolism. Due to its direct effect on cholesterol levels and cardiovascular health, diet quality is a critical component in the therapy of dyslipidaemia in the prevention and management of CVD.9 A diet’s quality can be defined as the degree to which its individual components contribute to good health. While individual nutrients, foods, and bioactive compounds may have targeted effects, it is the overall dietary pattern that exerts the most significant influence on health outcomes.10 Low quality diets characterised by high sugar and saturated fat content and insufficient intake of fruits and vegetables or fibre are inversely associated with healthy blood lipid levels and a higher risk of diseases, including CVD.11
In Bangladesh, where both CVD and dyslipidaemia rates are high,5 examining diet quality offers an opportunity to lower the risk of future cardiac events and improve overall prognosis in cardiac patients. While medications are commonly prescribed to manage dyslipidaemia, improving diet quality offers a complementary, sustainable and accessible approach to treatment for many patients, especially in resource-limited settings. Dietary interventions can empower healthcare providers to help patients make meaningful lifestyle changes that complement pharmacological treatments.
Assessing diet quality provides a comprehensive view of eating habits and their impact on health outcomes. One of the most comprehensive tools for evaluating diet quality is the Global Diet Quality Score (GDQS), which assesses dietary intake based on food groups and their contribution to nutrient sufficiency and chronic disease risk across different regions. The GDQS offers a more nuanced view than traditional diet metrics, as it considers a wider range of food groups and categorises foods into healthy and unhealthy categories based on their effects on health outcomes.12 The GDQS has been used previously in examining diet quality in relation to dyslipidaemia, providing actionable insights for dietary modifications that contribute to better lipid profiles.13 14
Despite the importance of diet in managing dyslipidaemia and preventing CVDs, there is a lack of research in Bangladesh on the potential link between dietary habits and lipid profiles of individuals with existing CVD. Addressing this gap is essential for understanding the dietary factors that contribute to dyslipidaemia in this population. Therefore, this study aims to evaluate diet quality and other factors associated with dyslipidaemia in cardiac patients in Bangladesh. The central hypothesis is that higher GDQSs, reflecting better diet quality, will be inversely associated with the odds of dyslipidaemia. By exploring the full range of factors, particularly dietary influences on lipid levels in CVD patients, this research seeks to inform more effective, personalised treatment approaches to manage dyslipidaemia and improve patient outcomes.
Materials and methods
Study area and study design
The study was conducted across two key medical facilities in Bangladesh, targeting a diverse patient population. Data were collected from the outpatient tertiary care unit of the National Institute of Cardiovascular Diseases (NICVD) hospital, located in Dhaka, and the coronary care unit of Sadar Hospital in Noakhali.
This cross-sectional study was carried out over a 10 month period, from January 2022 to October 2022. The inclusion criteria for this study were CVD patients aged 25 years and older, who had a confirmed diagnosis of CVD within the last 3 months by a medical doctor and were attending the selected hospitals for follow-up. Common types of CVD included coronary heart disease, cardiomyopathy, congenital heart disease, arrhythmia, rheumatic heart disease, heart failure and valvular heart disease.3 Exclusion criteria included pregnant and breastfeeding women, individuals under 25 years of age, hospitalised patients with CVD, chronic renal disease patients undergoing dialysis or kidney transplants, those in advanced stages (eGFR <15%), participants who failed to complete the questionnaire, and individuals lacking recent biochemical data.
The sample size was determined using the formula n=100 + 50 i, where i refers to number of independent variables in the final logistic regression model.15 Based on an assumption of nine independent variables in the regression model, the minimum required sample size was 550. To account for potential errors during the study process, an additional 5.0% was added, resulting in a total sample size of 570 participants.
Sociodemographic and biochemical characteristic variables
Participants completed self-reported questionnaires that included questions about their age, sex, education, income, employment status, health, dietary habits, smoking, alcohol consumption, and other socioeconomic and demographic factors. Additionally, blood lipid profile data (TC, LDL, HDL and TG) were extracted from participants’ recent biochemical report for further analysis. All the lipid profiles were analysed using enzymatic colourimetric methods, checked according to their report. Lipid profiles were classified according to Adult Treatment Panel III (ATP III) guidelines of the National Cholesterol Education Programme (NCEP, 2002).16 Dyslipidaemia was defined as having at least one of the following: total cholesterol ≥200 mg/dL, total triglycerides ≥150 mg/dL, LDL ≥130 mg/dL and HDL <40 mg/dL.16 Additionally, the lipid profiles were categorised as follows: elevated TG (TG ≥150 mg/dL), elevated TC (TC ≥200 mg/dL), elevated LDL (LDL ≥130 mg/dL) and low HDL (HDL <40 mg/dL).16 Hypertension was defined as systolic blood pressure (SBP) ≥140 mm Hg, diastolic blood pressure (DBP) ≥90 mm Hg and/or the use of antihypertensive drugs. Diabetes was defined as fasting blood plasma glucose level ≥7.0 mmol/L. Chronic kidney disease (CKD) was defined as a reduced glomerular filtration rate (GFR) of <60%.
Anthropometric measurements, including height and weight, were taken following standard procedures. BMI: kg/m2 was calculated by dividing participants' weight (in kg) by the square of their height (in m). BMI was categorised into four groups based on WHO guidelines: underweight (<18.5 kg/m2), normal weight (18.5–24.99 kg/m2), overweight (25.0–29.99 kg/m2) and obese (≥30.0 kg/m2). Smoking status was classified as either non-smoker or current smoker.
Nutrient and diet quality measurement
A previously validated semiquantitative food frequency questionnaire was administered to collect data from participants on their usual dietary intake over the past month. The questionnaire included 166 food items that are typical of both urban and rural Bangladeshis, as well as unique regional foods.17 To aid accurate portion estimation, participants were shown images of various portion sizes for the same food item. These images featured basic household portions, such as an empty bowl, plate, spoon or glass, and the participants were asked to indicate their usual portion size by selecting the appropriate level of fullness.
Nutrient and energy estimates were derived from dietary data of 122 out of the 166 food items based on the Food Composition Table (FCT) of Bangladesh.18 For food items not listed in the Bangladeshi FCT, composition data were supplemented from the Indian food composition table,19 and additional calculations were performed according to standard recipe compositions.
The GDQS was used to evaluate nutrient adequacy and examine the association between chronic diseases in a global context.20 The GDQS coding method categorises foods into 25 groups: 16 healthy food groups (eg, dark green/leafy/cruciferous/deep orange/other vegetables, deep orange fruits and tubers, citrus and other fruits, legumes, nuts and seeds, poultry and game meat, fish, whole grains, liquid oils, low-fat dairy and eggs), two unhealthy food groups when consumed in large quantities (high-fat dairy and red meat), and seven unhealthy food groups (eg, white roots and tubers, processed meats, refined grains and baked goods, sugar-sweetened beverages, sweets and ice cream). Healthy food categories received positive ratings, with higher scores reflecting greater consumption. Consuming less harmful food groups generally results in higher ratings, except for high-fat dairy and red meat, which scored better with moderate consumption and worse with very low or very high intakes. The GDQS was calculated according to standardised guidelines.12 20 The GDQS is the total score for all 25 food categories, ranging from 0 to 49 points (online supplemental annexure 1). Diet quality was classified as follows: high risk for poor diet quality (GDQS <15), moderate risk (GDQS: 15–22.99) and low risk (GDQS≥23).20
Supplemental material
Ethical consideration
This research was carried out with the authorisation of the FAHS Research Ethics Committee at DIU (Ref. No.: FAHSREC/DIU/2023/1109). Each participant provided informed consent and was made aware of their right to withdraw from the study at any time without facing any consequences.
Statistical method
Data was analysed statistically using SPSS 21.0. Continuous variables were shown as mean±SD, while categorical variables were given as frequency and percentage. When data were not normally distributed, the median (25 percentiles −75 percentiles) were used, and the Mann-Whitney U test was employed to assess differences between groups. A χ2 test was done to assess the association for categorical variables. GDQS were categorised into tertiles, where T1 indicated the lowest score and T3 showed the highest score. Linear trends across GDQS tertiles were estimated for elevated TC, elevated TG, elevated LDL, low HDL and dyslipidaemia and checked by the Cochran-Armitage test in STATA 13. Multivariate logistic regression analysis was used to identify independent predictors of dyslipidaemia, calculating AOR and 95% CIs. Variance inflation factors (VIF) were used to assess multicollinearity prior to performing multivariate logistic regression. VIF values below 2.2 indicated the lack of collinearity issues.21 The final logistic regression model included all variables with p values less than 0.25 in the bivariate analysis. Statistical significance was established as a p value less than 0.05.
Patient and public involvement
Patients and the public were not involved in the design, conduct, reporting, or dissemination plans of this research.
Results
Sociodemographic, anthropometric and clinical characteristics of the study participants
A total of 54.9% of the study participants were males. Most CVD patients were from rural areas andin middle-age groups. Over half of the study population (56.8%) had completed education only up to the primary school level, and 54.4% of participants reported a monthly income below 20 000 TK (table 1). Regarding occupation, only one-fourth of the participants were engaged in steady employment, while the remainder were either retired or homemakers. In terms of BMI distribution, 45.0% of participants were classified as overweight, 44.6% fell into the normal or underweight category, and 10.4% were obese. Additionally, comorbid conditions such as diabetes, hypertension and chronic kidney disease were observed in 40.0%, 74.0% and 30.0% of the participants, respectively (table 1). The majority of the study population (70.4%) exhibited dyslipidaemia (table 1). Among lipid abnormalities, hypercholesterolaemia (TC≥200 mg/dL) was the most prevalent, affecting 55.5% of participants, followed by hypertriglyceridaemia (TG ≥150 mg/dL, 52.2%), low HDL <40 mg/dL (40.9 %) and high LDL≥130 mg/dL (40.4%) (table 1).
General characteristics of the study subjects
Dyslipidaemia pattern in connection with other variables
Table 2 presents the distribution of CVD patients according to dyslipidaemia and its association with various sociodemographic and clinical variables. BMI, gender, income, education status, locality of the participants and hypertension were found to be statistically significant in different groups (dyslipidaemia vs non-dyslipidaemia) (table 2).
Associated factors for dyslipidaemia in cardiovascular disease (CVD) patients
Diet and nutrient intake of the participants
The nutrient intake patterns of the participants are summarised in table 3. The median intake of energy, protein and fat of the CVD patients was recorded at 1818 kcal, 62.8 g and 34.2 g, respectively. The non-dyslipidaemia group demonstrated significantly higher caloric intake and greater consumption of most nutrients, including both macronutrients and micronutrients, compared with the dyslipidaemia group (table 3).
Dietary nutrient intake pattern in different groups
Diet quality and associated factor for dyslipidaemia
The consumption levels of 25 GDQS food groups, categorised into three distinct groups, are presented in table 4. This table provides a detailed overview of the median consumption across various food categories, along with intake levels—low, medium and high for these food groups among individuals diagnosed with CVD.
Consumption of different food groups of the study subject and diet quality
Over 70% of patients with CVD reported limited consumption of foods from healthy food groups, including deep orange tubers, seeds and nuts, deep orange vegetables, low-fat dairy and cruciferous vegetables. Conversely, over 65% of the population exhibited high consumption of liquid oil and dark green leafy vegetables (table 4). Additionally, more than 70% of participants reported consuming fewer portions of several unhealthy foods, including processed meat, purchased deep-fried foods, sugar-sweetened beverages, juice, and white roots and tubers. The GDQS improves significantly when a high percentage of CVD patients consumed fewer unhealthy food groups. The non-dyslipidaemia group demonstrated significantly higher consumption of legumes, poultry and meat, as well as whole grains, in comparison to the dyslipidaemia group (online supplemental table 1).
Supplemental material
The mean GDQS for CVD patients was 24.38 (on a scale of 0–49), 69.8% of the population had a low-risk diet, while 30.20% and 0% had moderate and high-risk diet, respectively, according to GDQS cut-off points (table 4). The GDQS was significantly higher in the non-dyslipidaemia group (25.21±2.53) compared with the dyslipidaemia group (24.03±2.33) (table 4). Within the non-dyslipidaemia group, GDQS+ (ranging from 0 to 32) and GDQS (ranging from 0 to 17) were also higher compared with dyslipidaemia group, although only GDQS+was statistically significant.
GDQS was categorised into tertiles, with T1 representing the lowest scores (30.20 %) and T3 the highest (34.9%) (table 5). A significant trend was observed among elevated TC, elevated TG, elevated LDL and dyslipidaemia with GDQS (p value <0.001) (table 5). Hypercholesterolaemia, hypertriglyceridaemia, high LDL and dyslipidaemia were significantly associated with diet quality. Specifically, the odds of these conditions were significantly higher within the lowest tertile of GDQS compared with those on the highest tertile (table 5).
Univariate analysis for measuring association with GDQS and dyslipidaemia
The analytical results of the multivariable logistic regression are shown in table 6. Several factors, including sex, level of employment, BMI, hypertension and GDQS, were identified as potential contributory factors for lipid profile abnormalities (p value <0.05) in the multivariable logistic regression analysis (table 6). Male participants were more than four times as likely as female participants to have dyslipidaemia (AOR: 4.18, 95% CI 2.32 to 7.54). Regarding employment, participants who were retired or employed in services (AOR: 1.5, 95% CI 0.75 to 2.99, it will be = 0.253) and homemakers (AOR: 2.86, 95% CI 1.37 to 5.94, p value <0.005) had higher odds of developing dyslipidaemia compared with labourers. Participants with a BMI ≥30.0 (obese) were found to have higher odds of dyslipidaemia than overweight individuals (AOR: 0.43, 95% CI 0.21 to 0.91, it will be = 0.026). Finally, compared with the highest tertile of the GDQS in CVD patients, the odds of dyslipidaemia were nearly twice as high in the middle tertile (AOR: 1.87, 95% CI 1.13 to 3.11, p value=0.015) and almost four times higher in the lowest tertile (AOR: 3.67, 95% CI 2.02 to 6.64, p value <0.001) (table 6).
Model of multivariate logistic regression for the predation of dyslipidaemia
Discussion
This study aimed to assess the factors influencing dyslipidaemia in individuals with cardiac conditions, focusing on diet quality, consumption of healthy and unhealthy foods, as measured by the GDQS, and their relationship to dyslipidaemia among CVD patients in Bangladesh. The findings highlight significant associations between dyslipidaemia and various risk factors, including BMI, gender, occupation and diet quality. These results provide crucial insights into the characteristics and dietary intake patterns of cardiac patients with and without dyslipidaemia, offering valuable information for the development of targeted interventions and personalised dietary recommendations.
One key finding of this study is the strong association between higher BMI and the prevalence of dyslipidaemia. The data suggest that maintaining a healthy weight is essential for cardiac patients to manage and prevent dyslipidaemia. Previous research consistently links obesity with dyslipidaemia due to poor dietary choices and increased consumption of unhealthy fats and sugars, which contribute to lipid imbalances.22 23 Additionally, excess body weight can also contribute to free fatty acids, insulin resistance and inflammation, all of which are known to play a role in dyslipidaemia development.24
Gender differences in dyslipidaemia prevalence were also significant, with males being four times more likely to have dyslipidaemia than females. This finding aligns with earlier studies conducted in Bangladesh and globally.5 25 The lower prevalence of dyslipidaemia among females may be attributed to the protective effects of oestrogen on lipid metabolism, as oestrogen positively influences lipid profiles.26
Interestingly, occupation emerged as a significant factor, with homemakers being three times more likely to experience dyslipidaemia than other occupational groups. A survey in Karachi revealed that a significant percentage of homemakers were obese, largely due to unhealthy dietary practices, including frequent consumption of red meat, sweets and junk foods, coupled with a lack of physical activity.27 Thus, it suggests that homemakers may have greater access to unhealthy food options, which could contribute to poorer dietary habits and a higher incidence of dyslipidaemia. Social and cultural dynamics in Bangladesh may exacerbate this issue, as homemakers often prioritise the needs of their families over their own health, potentially increasing their vulnerability to dyslipidaemia and other non-communicable diseases.28 29
The results from this study highlight significant differences in dietary patterns between CVD patients with and without dyslipidaemia, as measured by the GDQS. Participants without dyslipidaemia had a healthier dietary pattern, as shown by their significantly higher GDQS and GDQS+. This indicates that a diet rich in nutrient-dense, heart-healthy foods is associated with better lipid profiles. Conversely, individuals in the lowest GDQS tertile had the highest likelihood of having elevated levels of LDL, triglycerides and total cholesterol. These findings align with previous studies, which have demonstrated an inverse association between diet quality scores and metabolic abnormalities including dyslipidaemia.13 30 For example, a previous study in Mexico discovered that higher GDQSs were associated with lower total and LDL cholesterol levels.31 Similarly, research in Iran32 and Sweden33 has shown that adherence to healthy eating guidelines, as indicated by various diet quality indices, correlates with improved lipid profiles. The mean GDQS of 24.38 observed in this study suggests a moderately healthy diet among the population, with the majority (69.8%) classified as having a low-risk diet. Notably, no participants fell into the high-risk group based on the GDQS cut-off points, indicating a positive trend in diet quality among CVD patients. In our analysis, consuming fewer unhealthy foods in the GDQS subcategory (GDQS−) did not affect the likelihood of dyslipidaemia because patients in both groups had similar low intakes of unhealthy items. This is also why the average GDQS was higher for the entire study population. This suggests that the presence of dyslipidaemia may be more strongly associated with the absence of positive dietary components, rather than the presence of unhealthy dietary factors. In other words, it is the inclusion of nutrient-dense, heart-healthy foods like whole grains, legumes and poultry among participants without dyslipidaemia that may play a more critical role in protecting against dyslipidaemia, rather than merely avoiding unhealthy foods. This finding aligns with previous research indicating that diets emphasising nutrient-dense foods are more effective at promoting cardiovascular health than those solely focused on reducing unhealthy food intake.14
Participants without dyslipidaemia reported significantly higher consumption of legumes, poultry and meat, and whole grains. These foods are rich in nutrients that contribute to improved lipid metabolism, such as fibre, B vitamins, MUFA and essential trace minerals such as copper, magnesium and zinc. Previous studies have shown that the consumption of viscous (soluble) dietary fibre from whole grains and legumes, along with the PUFAs and B vitamins, helps lower LDL cholesterol and triglycerides, which are key contributors to dyslipidaemia.16 Legumes, in particular, are rich in phytosterols, which have been proven to reduce total cholesterol, LDL cholesterol and atherogenic apolipoprotein levels.34 Essential trace minerals like zinc, copper and magnesium, present in lean poultry and legumes, are also vital in maintaining healthy cholesterol levels.35 36 These foods also provide vitamin B6, which helps regulate homocysteine levels, reducing the risk of increased biosynthesis and secretion of cholesterol and TG.37 MUFA found in poultry and some legumes help keep TG concentrations low.38 Lean meats (chicken/poultry), red meat or fish when consumed as part of a balanced diet, it can result in favourable changes in blood lipids, particularly reductions in total and LDL cholesterol.39 40 All these findings underscore the importance of a balanced and nutrient-rich diet in cardiac patients for reducing dyslipidaemia prevalence and promoting cardiovascular health. International dietary guidelines recommend increasing the consumption of vegetables, fruits, whole grains and lean meat.41 42 Raising awareness about the impact of dietary choices on lipid profiles can empower patients to adopt healthier eating habits, ultimately improving adherence to dietary recommendations and yielding long-term benefits.
The current research possesses both merits and drawbacks. To the best of our knowledge, this is the first investigation in Bangladesh that explores the relationship between dietary patterns and dyslipidaemia components, offering valuable evidence on the role of diet quality in the development of dyslipidaemia. However, as a cross-sectional study, it cannot establish causation but can only infer association. Dietary data were collected using a semiquantitative food frequency questionnaire (FFQ), which may be prone to measurement error and recall bias. Additionally, despite verifying participants’ medical records, some undiagnosed or incidental cases of dyslipidaemia may have been overlooked. The study also did not extensively control for the impact of lipid-lowering medications or other treatments for CVDs, which could affect lipid profiles independently of diet.
Future research should include larger, more diverse populations to enhance the generalisability of these findings. Investigating the impact of nutritional education and counselling on improving diet quality and managing dyslipidaemia could also provide more actionable insights. Addressing these limitations in future studies can lead to a more detailed and thorough understanding of the connection between diet quality and dyslipidaemia in CVD patients in Bangladesh.
Conclusion
This study highlights the critical role of diet quality in managing dyslipidaemia among CVD patients in Bangladesh, while also emphasising the importance of considering gender, BMI and occupational status in the development of comprehensive health interventions. By advocating for an integrated approach that addresses the multifaceted nature of dyslipidaemia through tailored dietary, lifestyle and policy interventions, it opens the door for more studies and prospective treatments in the field of cardiovascular health in Bangladesh, ultimately contributing to the global efforts in CVD prevention and health promotion. It is important for healthcare professionals to consider these risk factors when assessing patients for dyslipidaemia and developing appropriate interventions.
Data availability statement
Data are available upon reasonable request. All data are available in the manuscript.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved by This research was carried out with the authorization of the FAHS Research Ethics Committee at DIU (Ref. No.: FAHSREC/DIU/2023/1109) Participants gave informed consent to participate in the study before taking part.
References
Footnotes
Contributors TT and KMRK conceived and designed the experiments; performed the experiments; analysed and interpreted the data; wrote the paper; final approval of the version. CB analysed and interpreted the data; wrote the paper; final approval of the version. KMRK is responsible for the overall content as guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.