Addressing risk factors of Santals Adivasis: Policy recommendations for non-communicable diseases in Bangladesh

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Hafiz Iqbal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6002058/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background There is increasing evidence that rate of non-communicable diseases (NCDs) vary among different groups. However, studies related to disease burden and its risk factors among ethnic minorities are rare in Bangladesh. To fill this gap, our study explores the prevalence of various risk factors for major NCDs among Santal Adivasis and compares the interrelationship among different groups of risk factors. Methods Employing purposive sampling techniques, data were collected from 389 respondents in Birgonj Upazila of Dinajpur district through a pretested questionnaire. In addition to socio-demographic-anthropometric factors, laboratory diagnoses were conducted following standard techniques. Data were analyzed using univariate regression analysis. Results The prevalence of shared immediate risk factors for NCDs is remarkably low among Santal Adivasis . Among the modifiable intermediate risk factors, the use of tobacco and harmful alcohol consumption from early adulthood poses major risks for cardiovascular diseases in this population. Males appear to be more vulnerable to behavioral risk factors such as smoking and alcohol consumption, while a significantly higher proportion of females suffer from impaired glucose tolerance. Conclution The findings of this study emphasize the importance of targeted policies and interventions to improve health outcomes in this ethnic minority group. Non-communicable diseases Modifiable intermediate risk factors Socio-demographic-anthropometric factors Behavioral risk factor Ethnic minorities Figures Figure 1 Figure 2 Introduction Bangladesh, one of the most densely-populated countries in the world, is home to approximately 160 million people within a land area of 55,598 square miles (147,570 square km) [1]. Bangladesh has quite a few varieties of indigenous communities living in various parts of the country. About 1% of the population of Bangladesh consists of what are locally termed ‘tribal groups’ due to their distinct and unique languages, cultures, traditions, religions, and customs [2]. It consists of 54 indigenous communities speaking at least 35 different languages, alongside the majority Bengali population [3]. The isolation from mainstream development activities, together with a high level of poverty and difficult accessibility to the existing healthcare facilities, makes tribal communities specifically vulnerable to various health problems. Despite a large number of studies on health and healthcare-seeking behavior among the Bengali population in Bangladesh, relatively few studies have focused specifically on the tribal groups in the country. Tribal healthcare has predominantly focused on the prevalence of morbidity, profiles of illnesses, and health-provision coverage [1] rather than people's knowledge, practices, opinions and attitudes towards health provision in the tribal areas. The health and healthcare-seeking behavior of the Chattogram Hill Tract (CHT) population investigated the prevalence of morbidity and the differences in treatment-seeking among ethnic minorities and the Bengalis [4]. However, it lacks qualitative information on the perceived reasons for their choices of healthcare providers, their knowledge and opinions on health issues and services, and common practices based on traditional belief systems [1]. The crude prevalence of type 2 diabetes was 6.6%, and impaired fasting glucose (IFG) was 8.5% among tribal people in Khagrachari district [5]. Considering the socio-cultural, political, economic and topographical uniqueness of the tribal groups in Bangladesh, their healthcare needs, attitudes, and healthcare-seeking behaviors may differ from those of the Bengalis, Santals community of Sujalpur union in Birganj Upazila (the lowest administrative unit of Bangladesh) is no exception. Santals are known as one of the oldest ethnic groups of South Asia. Their skin color is dark, hair is black and smooth to wavy, they have broad nose with thick lips. Santals are of medium height. They form the largest tribal community in northern Bangladesh and primarily reside in the districts of Rajshahi, Rangpur, and Dinajpur. Most Santal villages are in remote places. There were approximately 150,000 Santal individuals in Bangladesh in 1984 [6]. However, updated information on the number of Santals cannot be provided due to the absence of a tribe-wise breakdown of national population census report. Given the scarcity of information and diverse life style, studying the Santals remains an important area of research. People of lower social and economic positions fare far worse in the case of non-communicable diseases (NCDs). Vulnerable and socially disadvantaged individual become sicker and die sooner due to NCDs compared to those in higher social positions [7]. The concept of health among the tribal communities significantly differs across various cultures. Culturally explainable phenomena related to tribal health have undergone both positive and negative changes in the era of globalization, which has introduced new traits and technological innovations. Ethnicity-based research can provide new insights into the pathogenesis of a disease, as the populations under study exhibit heterogeneity in genetic and lifestyle characteristics. There is mounting evidence that rates of cardiovascular disease vary among different ethnic groups [8, 9]. In India, the general health status of the tribal populations is known to be poor [10]. Factors such as widespread poverty, illiteracy, malnutrition, lack of safe drinking water, inadequate sanitary, and maternal and child healthcare services contribute to the challenging health conditions prevalent among tribal [11]. However, unlike India, very little research has been conducted on the tribal population in Bangladesh, particularly NCD risk factors. In the national survey on NCD risk factors in Bangladesh did not specifically address NCD risks among ethnic minority groups. In this context, the present study aims to determine the prevalence of NCDs risk factors, including dietary habits, cultural variations, and biological composition, among an important group of ethnic minorities- the Santals. There is no published data specifically focus on NCD risks among Santals, and in general, there are very few studies on their healthcare conditions. However, several questions remain: What are the non-modifiable risk factors for major NCDs among adult Santal Adivasis? What are the shared immediate risk factors for major NCDs among the study subjects? What are the shared modifiable intermediate risk factors for major NCDs present among the study subjects? What are the other shared primary risk factors for major NCDs among the study subjects? What are the interrelationships among various groups of risk factors among the study subjects? This study aims to provide immediate responses to these questions, exploring the prevalence of various risk factors related to major NCDs among Santal Adivasis and investigating the interrelationship among different risk factor groups. Additionally, the study has specific objectives, including identifying non-modifiable risk factors among adult Santal Adivasis, assessing shared immediate risk factors, determining shared modifiable intermediate risk factors, investigating other shared primary risk factors, and exploring interrelationships among risk factors. Methods Study area Sujalpur union of Birganj Upazila in Dinajpur district (Northern part of Bangladesh) was conveniently selected for data collection due to the availability of the Santals ethnic community (Fig. 1 ). Poverty, illiteracy, malnutrition, lack of pure drinking water, inadequate sanitary, and maternal and child healthcare (MCH) are the common features of this community. There are common beliefs that the blood from a mother’s uterus during delivery was unholy, leading to the mother and newborn being separated from the rest of the family for seven days post-delivery. The Santals are an indigenous ethnic group in this region, and their health challenges are multifaceted. For example, Santal women face institutional challenges in accessing healthcare. These include shortages of medicines at health facilities and absenteeism of health providers. The unequal attitude and behavior of healthcare providers toward Santal women contribute to limiting their access to healthcare. Traditionally, Santals have relied on indigenous healthcare practices. These practices may include herbal remedies and cultural beliefs related to health and illness. A significant proportion of Santals suffer from NCDs. These include conditions like cardiovascular disease, diabetes, and chronic lung disease. Sampling technique The study places were selected purposively. All Santals men and women aged 18 years or older of Sujalpur union who met the inclusion criteria were recruited by non-probability convenient sampling. Pregnant women, unwilling to participate, mentally challenged and institutionalized individual, and not resides in the study area were not included in our sampling. There were about 700 residents of santal population in the selected union. Among them about 450 residents were eligible to participate and finally 389 (87.11%) people were interviewed. Response rate of blood sample collection was around 70% (272 respondents) of the invited adults (Fig. 2 ) Ethical consideration Ethical approval was taken from Bangladesh University of Health Science (BUHS) Research Ethics Committee (Memo No. BUHS/ERC/EA/23/388). Informed consent was taken from each participant. Confidentiality of the participant was strictly maintained. Questionnaires and laboratory documents were kept securely and password protected. Autonomy was given to withdraw at any stage of the study. All the guidelines of Helsinki Declaration were followed. Data collection technique The participants were interviewed face to face by using semi-structured questionnaire. Informed consent was taken before interview and whole procedure was described prior to start interview. The interview took about 15–20 minutes including general information section, sociodemographic information included age, gender, religion, marital status, education, occupation, and economic status. Behavioral measurements included tobacco use, alcohol consumption, dietary habit, and physical activity. Furthermore, anthropometric measurements included height, weight, waist circumferences, hip circumferences, blood pressure measurement and biochemical tests section included fasting blood glucose, oral glucose tolerance test, and lipid profile. The participants were also asked about their medical history such as diabetes and hypertension. Ten field assistants from Dhaka (the capital city of Bangladesh) who were healthcare professionals were recruited for data collection. Training sessions were conducted for the field assistants for 4 days long (32 hours) prior to field work. The field assistants were trained for the field work which included sample selection, rapport building with the respondents, interview technique, anthropometric and blood pressure measurements. Each and every part of the questionnaire was described in details to the field assistants. Anthropometric measurements including height, weight, waist circumference, hip circumference, and blood pressure measurement were demonstrated. Group practice session and individual practice session were conducted for better field work. After that evaluation of every field assistant was done to check efficiency level. Finally evaluating competency level, the field assistants were recruited for the final work. Training sessions were properly guided by the facilitators and supervisors. Meeting with the local leaders and santal leaders was conducted for several times prior to start the field work. With the presence of the local and santal leaders’ discussion with the targeted population was also done to motivate them to participate in the study. After several sessions of meeting and discussion the field assistants were introduced to the santal community for field work. Finally with the help of some local santal people the field assistants started data collection from door to door. Field supervisors were also present all time during the field work to guide for any inconvenience. The field assistants gave a family identification number (e.g., FID-000) to each family and listed all the members aged 18 years or above belonging to that family. All the individuals selected for the study were given an identification number. The field assistants invited the potential participants for informed consent. The interviews and measurements were done at the household level. A cue card was given to the participant and requested to attend for the blood sample collection at the selected place for camp on a pre-arranged date after an overnight fast about 12 hours. During the data collection every participant was explained about the necessity of the fasting state for minimum of 12 hours prior to the test. After that participants were provided with 75gm glucose to drink and requested to wait for 2 hours without doing any heavy work. During the two-hour resting session participants were provided with heath education sessions. Efficient laboratory technician and scientific officers were recruited for blood sample collection and centrifuging Data were collected using a semi-structured questionnaire and checklist. A list of variables of interest was made in relation to the objectives and collateral appropriate questions and scales were developed. List of questionnaires was leaved out. The questions were constructed in simple Bangla. Pre-testing of questionnaire was done to see the understandability, time consumption, consistency of questions and acceptability. After reviewing the outcome of pre-testing, changes were incorporated accordingly. Checklist was used to record anthropometric measurements and laboratory data. Fasting and 2 hours after plasma glucose, triglyceride, total cholesterol, high-density lipoprotein (HDL) cholesterol were analyzed at Thakurgaon Swasthoseba Hospital.Glucose (Fasting and 2hrs after glucose) was measured by glucose Oxidase (GOD-PAP) method (Randox Laboratories Ltd. UK). Total cholesterol was measured by enzymatic laboratories, UK. Serum triglyceride was estimated by enzymatic colorimetric (GOD-PAP) method using reagents from Randox Laboratories, UK. Serum HDL-C was measured by enzymatic colorimetric (Cholesterol CHOD-PAP) Method (RANDOX Laboratories, UK). Survey through questionnaire and lab experiment were conducted during the whole year of 2021. All the estimations were carried out in an auto analyzer Hitachi 704. The low-density lipoprotein (LDL) cholesterol level in serum was calculated by using following formula. LDL-cholesterol = Total cholesterol-[1/5(Triglycerides) + HDL cholesterol] (1) Dietary pattern measuring tools (e.g., plate, glass, spoon, bowl, show cards, demy for different food items) were used to measure the quantity of food items. Measuring tapes were used to measure waist and hip circumferences. Height measuring tape were used to measure body height. Digital weight machines were used to measure body weight. Sphygmomanometers were used to measure blood pressure, and disposable syringes, cotton swabs, stripes, reagents were used for blood withdrawal. Data processing and analysis After collection, data were checked thoroughly for consistency and completeness. Individual questionnaire was checked and cleaned to avoid any possible mistakes. Data were initially checked on the day of collection to exclude any error or inconsistency or incompleteness. Data were categorized and coded during entry into the SPSS-17.0 software. It was started by the participant identification number and other properties of the variables. Then specific values were entered into each variable for each independent source of data. Data were cleaned by detection and correction of data set. Errors were detected by descriptive statistic, scatter plots and histograms for checking any missing data, normality and after removal of outliers again normality was checked. For proper empirical assessment, univariate, bivariate & multivariate analysis were done. Statistical associations between categorical variables were tested using chi-square (χ 2 ) test and mean difference of continuous variables by independent sample t- test to find out the association of socio-demographic status and the risk factors of interest. Results Descriptive statistics Out of 389 respondents, 184 (47.3%) were men and 205(52.7%) were women. Mean age of the respondents was 38.05 years with standard deviation (SD) of 15.26 years whereas the mean ± SD age of male and female were 39.11 ± 15.679 and 37.10 ± 14.853 respectively but the difference was not statistically significant ( p = 0.196 > 0.05) (see Table A1 in the appendix for more details). 213 (54.8) respondents were practiced Hinduism, where 98 (46%) were male and the rest 115 (54%) were female. In contrast, 176 respondents were practiced Christianity, where 86 (48.9%) were male and 90 (51.1%) were female. The religion distribution was not statistically significant because of higher p-value i.e., p = 0.611 > 0.05. Most of the participants (80.2%) were married, where male and female were 78.8% and 81.5%, and marital status showed strong statistical significance ( p = 0.0001 < 0.05). More than half (53%) of the respondents were farmer. Moreover 46.3% female and 22.3% male were housewife and day labor. Like marital status, strong statistical significance ( p = 0.0001 < 0.05) was seen among occupational distribution. About 54.2% respondents had no formal education where female and male distribution was 61% and 46.7% but in case of secondary and post-secondary level of education, male and female distribution was 14.1% and 11.7%, and mild statistical significance ( p = 0.038 < 0.05) was noted. Two-third of the participants (66.6%) represented from nuclear family. The mean ± SD monthly income of male and female in Taka (Bangladeshi currency) was 6929.35 ± 3875.862 and 7043 ± 4093.039, whereas monthly expenditure mean ± SD was 5340.22 ± 3312.951 and 5555.61 ± 3805.225 respectively. No statistical significance was seen in monthly income and expenditure. Table A2 in the appendix shows that about 63.6% and 26.6% of male was current and never smoker respectively whereas female distribution was 16.6% and 80% respectively and statistically it showed strong significance ( p = 0.0001 < 0.05). The mean ± SD of age of starting smoking was 18.51 ± 6.064 years. Female (92.7%) and male (64.4%) smoked bidi which was statistically significant ( p = 0.0001 < 0.05). The mean ± SD sticks consumed per day was 9.85 ± 5.752 ( p = 0.0001 < 0.05). About 65.3%, 30.8% and 3.9% respondents used smokeless tobacco ( p = 0.0001 < 0.05) and zorda (49.9%) was more prominent among other smokeless tobacco. Current alcohol drinker was more among male (53.3%) but never drinker was prominent among female (57.6%) and occasional drinker was quite similar both male and female and statistical significance ( p = 0.0001 < 0.05) was found. Regarding type of alcohol drinking local wine was very much popular. Mean age of starting alcohol was 18.74 years and mean frequency of alcohol drinking of last seven days was 2.56 as well as mean quantity of total intake of alcohol of last seven days was 1143.60. Frequency of alcohol drinking ( p = 0.004 < 0.05) and quantity of total intake of alcohol ( p = 0.0001 < 0.05) was statistically significant. Mean (± SD) energy intake of male and female was 768.66 (± 159.8) and 773.45 ± 155.74, respectively and in case of extra salt intake, nearly half of the respondents both male and female took extra salt and 35.9% male as well as 41.0% female did not take extra salt. Mean ± SD carbohydrate intake of male and female was 156.41 ± 31.53 and 156.81 ± 32.77 respectively. Mean ± SD protein intake of male and female was 23.22 ± 8.34and 22.66 ± 8.12 whereas mean ± SD fat intake was 4.39 ± 8.31 and 4.20 ± 5.48 respectively. In case of unhealthy diet like fatty rich food, empty caloric drink, street food, junk food and lack of fruit intake history did not find among the respondents. Table A3 in the appendix shows that soyabean oil intake among male and female was 68.5% and 71.2%, whereas mustard oil consumption was 31.5% and 28.8%, respectively whereas, mean ± SD oil intake was 2.11 ± 1.27 and 2.07 ± 1.32 respectively. The mean energy expenditure of male and female was 1965.66 and 1633.44 and it was strongly significant ( p = 0.0001 < 0.05). Males (76.1%) were more active than females (69.8%). Mean ± SD body mass index (BMI) of respondents was 20.01 ± 3.56. More than half of the respondent (55.5%) was normal in terms of BMI whereas underweight and obesity was 32.6% and 11.8% respectively. Mean waist hip ratio was 0.92 and almost all of them was normal. (Table A4 in the appendix) The mean (± SD) systolic blood pressure status of male and female was 109.26 (± 12.07) and 110.59 (± 38.35) respectively whereas diastolic blood pressure was 70.49 (± 10.44) and 70.25 (± 10.41) respectively. Most of the respondents both male and female had normal fasting blood glucose level. Mean (± SD) fasting blood glucose level among male and female was 4.48 (± 0.734) and 4.46 (± 0.755) mmol/L respectively. In case of oral glucose tolerance test (OGTT) test, most of the respondents found normal in terms of blood glucose level but IGT was 3.3% among male and 13.8% among female. Mean (± SD) of blood glucose among male and female was found 6.524 (± 1.133) and 6.675 (± 1.035) mmol/L respectively. Desirable and borderline cholesterol among male was 87.2% and 11.2% whereas 86.4% and 10.2% among female but high cholesterol was very low. Regarding HDL levels both male (80.8%) and female (76.2%) had high HDL but low HDL was negligible. Optimal, above optimal and borderline high LDL level among male and female was 41.6%, 34.4%, 20% and 46.3%, 29.3%, 18.4% respectively. In case of triglyceride most of male (89.6%) and female (87.8%) had normal level of triglyceride but high was minimal (Table A5 in the appendix). Most of the respondents (95%) had normal blood pressure and rest 5% were hypertensive. Among them, 88.40% respondents had normal systolic blood pressure followed by pre-hypertension (8%), hypertension stage 1 (2.10%) and hypertension stage 2 (1.50%). In addition, 91.50% respondents had normal diastolic blood pressure followed by pre-hypertension (2.3%), hypertension stage 1 (4.60%) and hypertension stage 2 (1.50%). Econometric estimation The econometric results involve systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, and BMI models (Table 1 ). All variables are assumed to follow a normal distribution. We evaluated the Log-likelihood (LL), Pseudo R-square, and Akaike information criterion (AIC) to assess model fit. A Log-likelihood value closer to zero indicates a decent model fit for choice experiment analysis. A Pseudo R-square greater than 0.20 suggests a well-fitted model. On the other hand, the smallest value of AIC indicates the best fitted model. Table 1. Results of estimated regression models for NCDs N.B. Standard errors in parenthesis, * p < 0.01, ** p < 0.05 Source: Authors’ calculation based on survey data, 2021 Significant association is found between age and systolic blood pressure. Likewise, there is statistically significant association between age and diastolic blood pressure, education and diastolic blood pressure, and monthly income and diastolic blood pressure. Religion has a great contribution to fasting blood glucose. On the other hand, martial status and monthly income are significant contributor to triglycerides, and education is a statistically influential factor of BMI. Positive sign of these variables (such as age, education, monthly income, and religion) is positively associated with few NCDs. According to [12] a standard Pseudo R-square takes the value ranging from 0.20–0.30. In this viewpoint, all of our NCDs model are decent. Discussion The current study indicated that most of the respondents (95%) had normal blood pressure and rest 5% had hypertensive. A population-based study done in the beginning of the decade found similar prevalence of hypertension (13%) [13], which was supportive to another population study in Bangladesh (12%) [14]. Recent studies done in rural community also suggested similar percentage [15]. Hypertension is a disease of its own as well as a risk factor for other major disease such as stroke, coronary heart disease, heart failure and renal insufficiency. It is very common in Bangladeshi people but its detection and treatment status are far from adequate. We should have intensive programme for salt reduction because its consumption is very high in the country. Estimated per capita salt intake based on salt production was 15.3 gm per day in 2001 [16], which is three times than a person requires for physiological functions of the body. This might be an important reason of high prevalence of hypertension in Bangladesh. A previous behavioral risk factor survey of NCDs in Bangladesh observed higher prevalence of table salt intake in both rural and urban areas. In rural area it was 92% and in urban area it was 46.3% [2]. Current study found that more than 50% of the study population took extra salt in term of table salt regularly which is a risk factor of high blood pressure. People in Bangladesh usually do not measure blood glucose level. 83% of the survey population never measured their blood glucose. Considering the prevalence of diabetes among those who measured blood glucose was 3.9%. In men the percentage is slightly high. Population data in Bangladesh indicate an increasing trend in diabetes prevalence especially in urban areas. A higher prevalence of diabetes mellitus in the urban population was also observed compared with rural subjects by another population-based study [17]. There are lines of evidences that the prevalence of diabetes is rising in Bangladesh [18]. In urban area the prevalence is just double (10%) [19]. But present study showed that most of the respondents both male and female had normal fasting blood glucose level. Mean ± SD fasting blood glucose level among male and female was 4.48 ± 0.734 and 4.46 ± 0.755 mmol/L, respectively. In case of OGTT test, most of the respondents found normal in terms of blood glucose level. Possible explanation for this may be their primitive lifestyle. Desirable and borderline cholesterol among male was 87.2% and 11.2% whereas 86.4% and 10.2% among female but high cholesterol was very low. Regarding HDL level both male (80.8%) and female (76.2%) had high HDL but low HDL was negligible. Optimal, above optimal and borderline high LDL level among male and female was 41.6%, 34.4%, 20%, and 46.3%, 29.3%, 18.4%, respectively. In case of triglyceride most of male (89.6%) and female (87.8%) had normal level of triglyceride but high was minimal. A study observed sub-optimal cholesterol level in over half of the sample and overall, the mean serum cholesterol levels in their sample were comparable to that in the United States [20]. Mean levels of HDL cholesterol and triglycerides were lower than in the United States. Consistent with the comparison of the mean levels, the prevalence of low HDL cholesterol was higher but the prevalence of high triglyceride levels lower than in the United States [21]. Obesity is believed by a section of the society to be a positive attribute, an indicator of a person's good health and prosperity. Evidence suggests that, in Bangladesh obesity is still not widely considered to be a health risk factor and in fact the converse, that losing weight is an indicator of illness, is more likely to be believed. This indicates that raising public awareness about the harmful consequences of obesity is necessary in order to influence societal norms concerning body size. Prevention and management of obesity are major challenges, especially in developing countries, where obesity often coexists with underweight. More than half of the respondents (55.5%) were normal in terms of BMI whereas underweight and overweight were 32.6% and 11.8% respectively whereas the national survey on NCD risk factors showed that one fourth of the population were underweight, 57% were normal and 18% were overweight. Similar findings were seen among several studies in Kuwait [22] and Saudi Arabia [23]. Actually, most of santal adibasis both men and women are hard worker and this tendency leads them to prevent overweight and obesity. Waist circumference provides an indication about the central obesity and has been suggested to be a risk factor more specific to cardiovascular disease as visceral fat is considered as a predictor of morbidity and mortality. This alone provides similar information as waist-hip ratio. Like general obesity the central obesity was also more in women. Overall, one in five had increased waist circumference. Recently waist circumference has been implicated with individual's propensity to develop NCDs. Higher prevalence of central and general adiposity in women indicates that women may be at a relatively increased risk of cardiovascular disease. Smoking habit was statistically significant in terms of smoking status, types of smoking, number of sticks consumed per day and smokeless tobacco. Almost half of the respondents had the habit of current smoking (45.2%) whereas NCD risk factor survey in Bangladesh found that the overall prevalence of smoking was 26.2%. From the data, we can see that prevalence of smoking is much higher in the study population. Smoking is clearly a major threat for health. A recent study conducted by [24] found that 41% of the eight killer diseases (heart attack, stroke, oral cancer, larynx cancer, lung cancer, Berger’s disease, tuberculosis and chronic obstructive pulmonary disease) are attributable to tobacco usage. Another study revealed that prevalence rate of daily smoking of 7.2% with variations among age, sex, religion and regions which findings were very much lower to current study [25]. Though consumption of alcohol is low in Bangladesh, due to sociocultural inhibition but this is quite ignored among ethnic communities because their sociocultural practice is different from Bengali people. The present study found that current alcohol drinker was more among male (53.3%) but never drinker was prominent among female (57.6%) and occasional drinker was quite similar in both males and females which was similar to the cross-sectional survey conducted among all the ethnic groups in Ethiopia with the WHO STEP wise approach [26]. This survey, therefore, identified large number of people with behavioral risk factors for NCDs that require immediate interventions and longer-term monitoring as a priority measure in Bangladesh. The prevalence of low physical activity was 27.2% among the study population whereas 27% of the mainstream population found to be in the low physical activity category. It shows that almost similar findings in case of physical inactivity. Mean age of the respondents was estimated at 38.05 years and [27] showed that mean age was 42.4 years which was quite similar with present study. Most of the participants were married. More than half (53%) of the respondents were farmer. [27] further reported in men farmers made up 22.8%, 19.2% were small businessmen, 12% were day laborer and 11.8% nongovernment employee. In women, housewives made up 83.4% of the surveyed population. Conclusion NCDs pose a significant global health burden. However, the prevalence and risk factors of NCDs among specific populations, such as Santal Adivasis , remain understudied. This study aims to summarize existing evidence on NCD risk factors in this population and highlight areas for further investigation. NCDs, including hypertension, diabetes, dyslipidemia, and obesity, contribute substantially to morbidity and mortality worldwide. Santal Adivasis, an indigenous community, exhibit unique health profiles. While shared immediate risk factors for NCDs are notably low among Santal Adivasis, there is a concerning prevalence of underweight individuals. The impact of underweight on NCD outcomes requires further exploration. The use of tobacco, particularly from early adulthood, emerges as a major risk factor for CVDs in Santal Adivasis , especially among males. Similar to tobacco, alcohol misuse contributes significantly to CVD risk in this population. Rather than the typical problem of positive energy balance seen in other populations, Santal Adivasis face undernutrition as a predominant dietary issue. Investigating its impact on NCDs is crucial. Understanding dietary patterns and food choices specific to this community is essential. As age increases, the prevalence of shared NCD risk factors rises. This trend warrants attention in preventive strategies. Santal males are more vulnerable to behavioral risk factors (e.g., smoking, alcohol consumption. Whereas, a higher proportion of Santa l females suffer from IGT, an important NCD risk factor. Further research is needed to comprehensively assess NCD prevalence, risk factors, and outcomes among Santal Adivasis. Policymakers and health practitioners should consider these findings to tailor interventions effectively. Abbreviations SD : Standard deviation SPSS: Statistical package for the social sciences Declarations Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgements All authors express their sincere gratitude to the anonymous reviewers for their valuable comments and suggestions. They also extend their appreciation to all respondents for generously providing insightful data and information, which significantly contributed to the successful completion of this work. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author information Authors and Affiliations Bangladesh University of Health Science, Dhaka 1216, Bangladesh Sharmin Sultana Tel.: +66(0) 91-704-3684; E-mail: [email protected] ORCID ID: 0009-0003-6236-7860 Government Edward College, Pabna 6600, Bangladesh Md. Hafiz Iqbal, PhD Tel.: +880-1717-278232; +880-1776-196953; E-mail: [email protected] ORCID: 0000-0001-6181-1980 Contributions SS: Conceptualization, Methodology, Software, Data curation, Formal Analysis, and Original draft preparation. MHI: Validation, Visualization, Investigation, Visualization, Supervision, review and editing . Corresponding author(s) Correspondence to Sharmin Sultana and Md. Hafiz Iqbal Ethics declaration This study was reviewed and approved by the Bangladesh University of Health Science (BUHS) Research Ethics Committee (Reference number: BUHS/ERC/EA/23/388). Ethical standards outlined in the Declaration of Helsinki and its subsequent amendments were followed, ensuring confidentiality and voluntary participation. All participants provided informed consent before the survey, and were free to withdraw at any time without explanation. To guarantee anonymity, no personal identifiers were collected, and all responses remained confidential. Participants confirmed their consent by checking a box indicating they had read, understood, and agreed to the terms of participation. Contact details for the researchers were provided for any inquiries. Competing interest The authors declare that they have no competing interests related to the research, authorship, and/or publication of this article. References Rahman SA, Kielmann T, McPake B, Normand C. 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Available from: https://doi.org/10.1186/s12889-019-7335-7 Sayeed MA, Mahtab H, Khanam PA, Ahsan KA, Banu A, Rashid AB, Khan AA. 2004. Diabetes and impaired fasting glycemia in the tribes of Khagrachari hill tracts of Bangladesh. Diabetes Care. 2004; 27 (5):1054-1059. Available from https://doi.org/10.2337/diacare.27.5.1054 Tithi FA, Basanta KB, Sanzidur R. Income Inequality, Poverty and Food Security of Plain Land Ethnic Communities of Bangladesh. Asian Development Perspectives (ADP ) . 2020; 11(1): 16-32. Available from https://doi.org/10.22681/ADP.2020.11.1.16 Iqbal MH. Disparities of health services for the poor in the coastal area: does universal health coverage reduce disparities? Journal of Market Access & Health Policy.2019; 7(1): 1575683. Available from https://doi.org/10.1080/20016689.2019.1575683 Grines CL, Klein AJ, Bauser‐Heaton H, Alkhouli M, Katukuri N, Aggarwal V, Altin SE, Batchelor WB, Blankenship JC, Fakorede F, Hawkins B. 2021. Racial and ethnic disparities in coronary, vascular, structural, and congenital heart disease. Catheterization and Cardiovascular Interventions. 2021; 98 (2): 277-294. Available from: https://doi.org/10.1002/ccd.29745 Ravid JD, Kamel MH, Chitalia VC. Uraemic solutes as therapeutic targets in CKD-associated cardiovascular disease. Nature Reviews Nephrology. 2021; 17 (6): 402-416. Available from https://doi.org/10.1038/s41581-021-00408-4 Adhikari T, Yadav J, Tripathi N, Tolani H, Kaur H, Rao MVV. Do tribal children experience elevated risk of poor nutritional status in India? A multilevel analysis. Journal of Biosocial Science. 2021; 53(5):683-708. Available from: https://doi.org/10.1017/S0021932020000474 Lakhanpaul M, Roy S, Benton L, Lall M, Khanna R, Vijay VK, Sharma S, Manikam L, Santwani N, Reddy H, Chaturvedi H. 2022. Why India is struggling to feed their young children? A qualitative analysis for tribal communities. BMJ Open. 2022; 12(7): e051558. Available from: https:// doi.org/ 10.1136/bmjopen-2021-051558 Louviere JJ, Hensher DA, Swait JD. Stated choice methods: analysis and applications . 2000; University Press, UK: Cambridge. Abebe AT, Kebede YT, Mohammed BD. An Assessment of the Prevalence and Risk Factors of Hypertensive Crisis in Patients Who Visited the Emergency Outpatient Department (EOPD) at Adama Hospital Medical College, Adama, Oromia, Ethiopia: A 6‐Month Prospective Study. International Journal of Hypertension. 2024; 1:6893267. Available from: https://doi.org/10.1155/2024/6893267 Hasan M, Khan MSA, Sutradhar I, Hossain MM, Hossaine M, Yoshimura Y, Choudhury SR, Sarker M, Mridha MK. Prevalence and associated factors of hypertension in selected urban and rural areas of Dhaka, Bangladesh: findings from SHASTO baseline survey. BMJ Open. 2021; 11(1): e038975. Available from https://doi.org/10.1136/bmjopen-2020-038975 Islam JY, Zaman MM, Ahmed JU, Choudhury SR, Khan H, Zissan T. 2020. Sex differences in prevalence and determinants of hypertension among adults: a cross-sectional survey of one rural village in Bangladesh. BMJ Open. 2020; 10 (9): e037546. Available from https://doi.org/ doi: 10.1136/bmjopen-2020-037546 Andarwulan N, Madanijah S, Briawan D, Anwar K, Bararah A, Średnicka-Tober D. 2021. Food consumption pattern and the intake of sugar, salt, and fat in the South Jakarta City—Indonesia. Nutrients. 2021; 13 (4): 1289. Available from https://doi.org/10.3390/nu13041289 Ayele BH, Roba HS, Beyene AS, Mengesha MM. 2020. Prevalent, uncontrolled, and undiagnosed diabetes mellitus among urban adults in Dire Dawa, Eastern Ethiopia: A population-based cross-sectional study. SAGE Open Medicine. 2020; 8 :2050312120975235.Available from https://doi.org/10.1177/2050312120975235 Talukder A, Hossain MZ. Prevalence of diabetes mellitus and its associated factors in Bangladesh: application of two-level logistic regression model. Scientific Reports. 2020; 10(1): 10237. Available from: https://doi.org/10.1038/s41598-020-66084-9 Khan JR, Sultana A, Islam MM, Biswas RK. A negative association between prevalence of diabetes and urban residential area greenness detected in nationwide assessment of urban Bangladesh. Scientific Reports. 2021; 11(1):19513. Available from https://doi.org/10.1038/s41598-021-98585-6 Weng SF, Akyea RK, Man KK, Lau WC, Iyen B, Blais JE, Chan EW, Siu CW, Qureshi N, Wong IC, Kai J. 2021. Determining propensity for sub-optimal low-density lipoprotein cholesterol response to statins and future risk of cardiovascular disease. Plos One. 2021; 16 (12): e0260839. Available from: https://doi.org/10.1371/journal.pone.0260839 Cannon CP, de Lemos JA, Rosenson RS, Ballantyne CM, Liu Y, Yazdi D, Elliott-Davey M, Mues KE, Bhatt DL, Kosiborod MN, GOULD Investigators. 2020. Getting to an ImprOved Understanding of Low-Density Lipoprotein-Cholesterol and Dyslipidemia Management (GOULD): Methods and baseline data of a registry of high cardiovascular risk patients in the United States. American Heart Journal. 2020; 219 : 70-77. Available from: https://doi.org/10.1016/j.ahj.2019.10.014 Oguoma VM, Coffee NT, Alsharrah S, Abu-Farha M, Al-Refaei FH, Al-Mulla F, Daniel M. Prevalence of overweight and obesity, and associations with socio-demographic factors in Kuwait. BMC Public Health. 2021; 21 : 1-13. Available from: https://doi.org/10.1186/s12889-021-10692-1 Aljaadi AM, Alharbi M. Overweight and obesity among saudi children: prevalence, lifestyle factors, and health impacts. Handbook of Healthcare in the Arab World. 2021; 1155-1179. Available from: https://doi.org/10.1007/978-3-030-36811-1_187 Neuberger M. Tobacco and alternative nicotine products and their regulation. Regulatory Toxicology. 2021; 1127-1151. Available from https://doi.org/10.1007/978-3-030-57499-4_124 Martinez EZ, Giglio FM, Terada NAY, da Silva AS, Zucoloto ML. 2017. Smoking prevalence among users of primary healthcare units in Brazil: the role of religiosity. Journal of Religion and Health. 2017; 56 : 2180-2193. Available from https://doi.org/10.1007/s10943-017-0389-x Ejigu BA, Tiruneh FN. 2023. The Link between Overweight/Obesity and Noncommunicable Diseases in Ethiopia: Evidences from Nationwide WHO STEPS Survey 2015. International Journal of Hypertension. 2023; 1: 2199853. Available from: https://doi.org/10.1155/2023/2199853 Riaz BK, Islam MZ, Islam AS, Zaman MM, Hossain MA, Rahman MM, Khanam F, Amin, KB, Noor IN. Risk factors for non-communicable diseases in Bangladesh: findings of the population-based cross-sectional national survey 2018. BMJ Open. 2020; 10(11): e041334. https://doi.org/ doi:10.1136/bmjopen-2020-041334 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6002058","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":415816390,"identity":"364f23c4-d219-42f5-8b98-0624e8c12160","order_by":0,"name":"Sharmin Sultana","email":"","orcid":"","institution":"Bangladesh University of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sharmin","middleName":"","lastName":"Sultana","suffix":""},{"id":415816391,"identity":"e7723212-3451-418b-9050-67173600f104","order_by":1,"name":"Md. Hafiz Iqbal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYHACZiCWYDBgYG58AGTx8JGghbHZAKSFjUgtDCAtbRIgBkEtBsePPzb4uMdCdjv7wbbKrzl2MmwMzA8f3cCn5UyOceKMZxLGO3sS227LbksGOozN2DgHjxbJhhzmwzwHJBI3HABqkdzGDNTCwyaNV0v/88cQLecfthVLbqsnrIVfIsE4GazlRmIb48dth4nR8sbYcMYBoF9mPGyWZtx2nIeNmYBf2PjTH0t8OFAnu50/+eDHn9uq7fnZmx8+xqcFBhgbgAQzD4jJTIRyuBbGH0SqHgWjYBSMgpEFAPbiR/Jpj9FNAAAAAElFTkSuQmCC","orcid":"","institution":"Government Edward College, Pabna 6600, Bangladesh","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"Hafiz","lastName":"Iqbal","suffix":""}],"badges":[],"createdAt":"2025-02-10 20:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6002058/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6002058/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76475605,"identity":"17aa6bdc-ac3a-418b-ba23-52b507847df4","added_by":"auto","created_at":"2025-02-17 13:49:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1521118,"visible":true,"origin":"","legend":"\u003cp\u003eStudy area.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u003c/strong\u003ePrepared by the authors, 2021\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6002058/v1/c99c8fa020988642a51578db.png"},{"id":76475607,"identity":"e966db46-c95e-40b4-a4e2-8437f116ed38","added_by":"auto","created_at":"2025-02-17 13:49:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":290225,"visible":true,"origin":"","legend":"\u003cp\u003eAlgorithm for selection of study sample\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource: \u003c/strong\u003ePrepared by the authors, 2021\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6002058/v1/f9e91e04ee0204c47df5f054.png"},{"id":76671605,"identity":"5a8ebee9-f032-4acd-9211-6f9cbaf53e9f","added_by":"auto","created_at":"2025-02-19 13:39:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2284602,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6002058/v1/6e6a9939-f362-4862-af09-b518e71f2a54.pdf"},{"id":76475603,"identity":"32c9003a-0d61-4475-ab96-11175f8930ed","added_by":"auto","created_at":"2025-02-17 13:49:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42851,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6002058/v1/fc2a8118734d97fc6de14f76.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Addressing risk factors of Santals Adivasis: Policy recommendations for non-communicable diseases in Bangladesh","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBangladesh, one of the most densely-populated countries in the world, is home to approximately 160\u0026nbsp;million people within a land area of 55,598 square miles (147,570 square km) [1]. Bangladesh has quite a few varieties of indigenous communities living in various parts of the country. About 1% of the population of Bangladesh consists of what are locally termed \u0026lsquo;tribal groups\u0026rsquo; due to their distinct and unique languages, cultures, traditions, religions, and customs [2]. It consists of 54 indigenous communities speaking at least 35 different languages, alongside the majority Bengali population [3]. The isolation from mainstream development activities, together with a high level of poverty and difficult accessibility to the existing healthcare facilities, makes tribal communities specifically vulnerable to various health problems. Despite a large number of studies on health and healthcare-seeking behavior among the Bengali population in Bangladesh, relatively few studies have focused specifically on the tribal groups in the country. Tribal healthcare has predominantly focused on the prevalence of morbidity, profiles of illnesses, and health-provision coverage [1] rather than people's knowledge, practices, opinions and attitudes towards health provision in the tribal areas. The health and healthcare-seeking behavior of the Chattogram Hill Tract (CHT) population investigated the prevalence of morbidity and the differences in treatment-seeking among ethnic minorities and the Bengalis [4]. However, it lacks qualitative information on the perceived reasons for their choices of healthcare providers, their knowledge and opinions on health issues and services, and common practices based on traditional belief systems [1]. The crude prevalence of type 2 diabetes was 6.6%, and impaired fasting glucose (IFG) was 8.5% among tribal people in Khagrachari district [5]. Considering the socio-cultural, political, economic and topographical uniqueness of the tribal groups in Bangladesh, their healthcare needs, attitudes, and healthcare-seeking behaviors may differ from those of the Bengalis, Santals community of Sujalpur union in Birganj \u003cem\u003eUpazila\u003c/em\u003e (the lowest administrative unit of Bangladesh) is no exception.\u003c/p\u003e \u003cp\u003eSantals are known as one of the oldest ethnic groups of South Asia. Their skin color is dark, hair is black and smooth to wavy, they have broad nose with thick lips. Santals are of medium height. They form the largest tribal community in northern Bangladesh and primarily reside in the districts of Rajshahi, Rangpur, and Dinajpur. Most Santal villages are in remote places. There were approximately 150,000 Santal individuals in Bangladesh in 1984 [6]. However, updated information on the number of Santals cannot be provided due to the absence of a tribe-wise breakdown of national population census report. Given the scarcity of information and diverse life style, studying the Santals remains an important area of research.\u003c/p\u003e \u003cp\u003ePeople of lower social and economic positions fare far worse in the case of non-communicable diseases (NCDs). Vulnerable and socially disadvantaged individual become sicker and die sooner due to NCDs compared to those in higher social positions [7]. The concept of health among the tribal communities significantly differs across various cultures. Culturally explainable phenomena related to tribal health have undergone both positive and negative changes in the era of globalization, which has introduced new traits and technological innovations. Ethnicity-based research can provide new insights into the pathogenesis of a disease, as the populations under study exhibit heterogeneity in genetic and lifestyle characteristics. There is mounting evidence that rates of cardiovascular disease vary among different ethnic groups [8, 9]. In India, the general health status of the tribal populations is known to be poor [10]. Factors such as widespread poverty, illiteracy, malnutrition, lack of safe drinking water, inadequate sanitary, and maternal and child healthcare services contribute to the challenging health conditions prevalent among tribal [11]. However, unlike India, very little research has been conducted on the tribal population in Bangladesh, particularly NCD risk factors. In the national survey on NCD risk factors in Bangladesh did not specifically address NCD risks among ethnic minority groups. In this context, the present study aims to determine the prevalence of NCDs risk factors, including dietary habits, cultural variations, and biological composition, among an important group of ethnic minorities- the Santals. There is no published data specifically focus on NCD risks among Santals, and in general, there are very few studies on their healthcare conditions. However, several questions remain: What are the non-modifiable risk factors for major NCDs among adult Santal Adivasis? What are the shared immediate risk factors for major NCDs among the study subjects? What are the shared modifiable intermediate risk factors for major NCDs present among the study subjects? What are the other shared primary risk factors for major NCDs among the study subjects? What are the interrelationships among various groups of risk factors among the study subjects? This study aims to provide immediate responses to these questions, exploring the prevalence of various risk factors related to major NCDs among Santal Adivasis and investigating the interrelationship among different risk factor groups. Additionally, the study has specific objectives, including identifying non-modifiable risk factors among adult Santal Adivasis, assessing shared immediate risk factors, determining shared modifiable intermediate risk factors, investigating other shared primary risk factors, and exploring interrelationships among risk factors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy area\u003c/h2\u003e\n \u003cp\u003eSujalpur union of Birganj \u003cem\u003eUpazila\u003c/em\u003e in Dinajpur district (Northern part of Bangladesh) was conveniently selected for data collection due to the availability of the Santals ethnic community (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Poverty, illiteracy, malnutrition, lack of pure drinking water, inadequate sanitary, and maternal and child healthcare (MCH) are the common features of this community. There are common beliefs that the blood from a mother\u0026rsquo;s uterus during delivery was unholy, leading to the mother and newborn being separated from the rest of the family for seven days post-delivery. The Santals are an indigenous ethnic group in this region, and their health challenges are multifaceted. For example, Santal women face institutional challenges in accessing healthcare. These include shortages of medicines at health facilities and absenteeism of health providers. The unequal attitude and behavior of healthcare providers toward Santal women contribute to limiting their access to healthcare. Traditionally, Santals have relied on indigenous healthcare practices. These practices may include herbal remedies and cultural beliefs related to health and illness. A significant proportion of Santals suffer from NCDs. These include conditions like cardiovascular disease, diabetes, and chronic lung disease.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSampling technique\u003c/h3\u003e\n\u003cp\u003eThe study places were selected purposively. All Santals men and women aged 18 years or older of Sujalpur union who met the inclusion criteria were recruited by non-probability convenient sampling. Pregnant women, unwilling to participate, mentally challenged and institutionalized individual, and not resides in the study area were not included in our sampling. There were about 700 residents of santal population in the selected union. Among them about 450 residents were eligible to participate and finally 389 (87.11%) people were interviewed. Response rate of blood sample collection was around 70% (272 respondents) of the invited adults (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eEthical consideration\u003c/h3\u003e\n\u003cp\u003eEthical approval was taken from Bangladesh University of Health Science (BUHS) Research Ethics Committee (Memo No. BUHS/ERC/EA/23/388). Informed consent was taken from each participant. Confidentiality of the participant was strictly maintained. Questionnaires and laboratory documents were kept securely and password protected. Autonomy was given to withdraw at any stage of the study. All the guidelines of Helsinki Declaration were followed.\u003c/p\u003e\n\u003ch3\u003eData collection technique\u003c/h3\u003e\n\u003cp\u003eThe participants were interviewed face to face by using semi-structured questionnaire. Informed consent was taken before interview and whole procedure was described prior to start interview. The interview took about 15\u0026ndash;20 minutes including general information section, sociodemographic information included age, gender, religion, marital status, education, occupation, and economic status. Behavioral measurements included tobacco use, alcohol consumption, dietary habit, and physical activity. Furthermore, anthropometric measurements included height, weight, waist circumferences, hip circumferences, blood pressure measurement and biochemical tests section included fasting blood glucose, oral glucose tolerance test, and lipid profile. The participants were also asked about their medical history such as diabetes and hypertension.\u003c/p\u003e\n\u003cp\u003eTen field assistants from Dhaka (the capital city of Bangladesh) who were healthcare professionals were recruited for data collection. Training sessions were conducted for the field assistants for 4 days long (32 hours) prior to field work. The field assistants were trained for the field work which included sample selection, rapport building with the respondents, interview technique, anthropometric and blood pressure measurements. Each and every part of the questionnaire was described in details to the field assistants. Anthropometric measurements including height, weight, waist circumference, hip circumference, and blood pressure measurement were demonstrated. Group practice session and individual practice session were conducted for better field work. After that evaluation of every field assistant was done to check efficiency level. Finally evaluating competency level, the field assistants were recruited for the final work. Training sessions were properly guided by the facilitators and supervisors.\u003c/p\u003e\n\u003cp\u003eMeeting with the local leaders and santal leaders was conducted for several times prior to start the field work. With the presence of the local and santal leaders\u0026rsquo; discussion with the targeted population was also done to motivate them to participate in the study. After several sessions of meeting and discussion the field assistants were introduced to the santal community for field work. Finally with the help of some local santal people the field assistants started data collection from door to door. Field supervisors were also present all time during the field work to guide for any inconvenience.\u003c/p\u003e\n\u003cp\u003eThe field assistants gave a family identification number (e.g., FID-000) to each family and listed all the members aged 18 years or above belonging to that family. All the individuals selected for the study were given an identification number. The field assistants invited the potential participants for informed consent. The interviews and measurements were done at the household level. A cue card was given to the participant and requested to attend for the blood sample collection at the selected place for camp on a pre-arranged date after an overnight fast about 12 hours. During the data collection every participant was explained about the necessity of the fasting state for minimum of 12 hours prior to the test. After that participants were provided with 75gm glucose to drink and requested to wait for 2 hours without doing any heavy work. During the two-hour resting session participants were provided with heath education sessions. Efficient laboratory technician and scientific officers were recruited for blood sample collection and centrifuging\u003c/p\u003e\n\u003cp\u003eData were collected using a semi-structured questionnaire and checklist. A list of variables of interest was made in relation to the objectives and collateral appropriate questions and scales were developed. List of questionnaires was leaved out. The questions were constructed in simple Bangla. Pre-testing of questionnaire was done to see the understandability, time consumption, consistency of questions and acceptability. After reviewing the outcome of pre-testing, changes were incorporated accordingly. Checklist was used to record anthropometric measurements and laboratory data.\u003c/p\u003e\n\u003cp\u003eFasting and 2 hours after plasma glucose, triglyceride, total cholesterol, high-density lipoprotein (HDL) cholesterol were analyzed at Thakurgaon Swasthoseba Hospital.Glucose (Fasting and 2hrs after glucose) was measured by glucose Oxidase (GOD-PAP) method (Randox Laboratories Ltd. UK). Total cholesterol was measured by enzymatic laboratories, UK. Serum triglyceride was estimated by enzymatic colorimetric (GOD-PAP) method using reagents from Randox Laboratories, UK. Serum HDL-C was measured by enzymatic colorimetric (Cholesterol CHOD-PAP) Method (RANDOX Laboratories, UK). Survey through questionnaire and lab experiment were conducted during the whole year of 2021. All the estimations were carried out in an auto analyzer Hitachi 704. The low-density lipoprotein (LDL) cholesterol level in serum was calculated by using following formula.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLDL-cholesterol\u0026thinsp;=\u0026thinsp;Total cholesterol-[1/5(Triglycerides)\u0026thinsp;+\u0026thinsp;HDL cholesterol]\u003c/em\u003e (1)\u003c/p\u003e\n\u003cp\u003eDietary pattern measuring tools (e.g., plate, glass, spoon, bowl, show cards, demy for different food items) were used to measure the quantity of food items. Measuring tapes were used to measure waist and hip circumferences. Height measuring tape were used to measure body height. Digital weight machines were used to measure body weight. Sphygmomanometers were used to measure blood pressure, and disposable syringes, cotton swabs, stripes, reagents were used for blood withdrawal.\u003c/p\u003e\n\u003ch3\u003eData processing and analysis\u003c/h3\u003e\n\u003cp\u003eAfter collection, data were checked thoroughly for consistency and completeness. Individual questionnaire was checked and cleaned to avoid any possible mistakes. Data were initially checked on the day of collection to exclude any error or inconsistency or incompleteness. Data were categorized and coded during entry into the SPSS-17.0 software. It was started by the participant identification number and other properties of the variables. Then specific values were entered into each variable for each independent source of data. Data were cleaned by detection and correction of data set. Errors were detected by descriptive statistic, scatter plots and histograms for checking any missing data, normality and after removal of outliers again normality was checked. For proper empirical assessment, univariate, bivariate \u0026amp; multivariate analysis were done. Statistical associations between categorical variables were tested using chi-square (\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e test and mean difference of continuous variables by independent sample t- test to find out the association of socio-demographic status and the risk factors of interest.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eDescriptive statistics\u003c/h2\u003e\n \u003cp\u003eOut of 389 respondents, 184 (47.3%) were men and 205(52.7%) were women. Mean age of the respondents was 38.05 years with standard deviation (SD) of 15.26 years whereas the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD age of male and female were 39.11\u0026thinsp;\u0026plusmn;\u0026thinsp;15.679 and 37.10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.853 respectively but the difference was not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.196\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (see Table \u003cspan class=\"InternalRef\"\u003eA1\u003c/span\u003e in the appendix for more details).\u003c/p\u003e\n \u003cp\u003e213 (54.8) respondents were practiced Hinduism, where 98 (46%) were male and the rest 115 (54%) were female. In contrast, 176 respondents were practiced Christianity, where 86 (48.9%) were male and 90 (51.1%) were female. The religion distribution was not statistically significant because of higher p-value i.e., \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.611\u0026thinsp;\u0026gt;\u0026thinsp;0.05. Most of the participants (80.2%) were married, where male and female were 78.8% and 81.5%, and marital status showed strong statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05). More than half (53%) of the respondents were farmer. Moreover 46.3% female and 22.3% male were housewife and day labor. Like marital status, strong statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was seen among occupational distribution. About 54.2% respondents had no formal education where female and male distribution was 61% and 46.7% but in case of secondary and post-secondary level of education, male and female distribution was 14.1% and 11.7%, and mild statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was noted. Two-third of the participants (66.6%) represented from nuclear family. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD monthly income of male and female in \u003cem\u003eTaka\u003c/em\u003e (Bangladeshi currency) was 6929.35\u0026thinsp;\u0026plusmn;\u0026thinsp;3875.862 and 7043\u0026thinsp;\u0026plusmn;\u0026thinsp;4093.039, whereas monthly expenditure mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD was 5340.22\u0026thinsp;\u0026plusmn;\u0026thinsp;3312.951 and 5555.61\u0026thinsp;\u0026plusmn;\u0026thinsp;3805.225 respectively. No statistical significance was seen in monthly income and expenditure.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003eA2\u003c/span\u003e in the appendix shows that about 63.6% and 26.6% of male was current and never smoker respectively whereas female distribution was 16.6% and 80% respectively and statistically it showed strong significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD of age of starting smoking was 18.51\u0026thinsp;\u0026plusmn;\u0026thinsp;6.064 years. Female (92.7%) and male (64.4%) smoked bidi which was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD sticks consumed per day was 9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.752 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05). About 65.3%, 30.8% and 3.9% respondents used smokeless tobacco (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and zorda (49.9%) was more prominent among other smokeless tobacco. Current alcohol drinker was more among male (53.3%) but never drinker was prominent among female (57.6%) and occasional drinker was quite similar both male and female and statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was found. Regarding type of alcohol drinking local wine was very much popular. Mean age of starting alcohol was 18.74 years and mean frequency of alcohol drinking of last seven days was 2.56 as well as mean quantity of total intake of alcohol of last seven days was 1143.60. Frequency of alcohol drinking (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and quantity of total intake of alcohol (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was statistically significant. Mean (\u0026plusmn;\u0026thinsp;SD) energy intake of male and female was 768.66 (\u0026plusmn;\u0026thinsp;159.8) and 773.45\u0026thinsp;\u0026plusmn;\u0026thinsp;155.74, respectively and in case of extra salt intake, nearly half of the respondents both male and female took extra salt and 35.9% male as well as 41.0% female did not take extra salt.\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD carbohydrate intake of male and female was 156.41\u0026thinsp;\u0026plusmn;\u0026thinsp;31.53 and 156.81\u0026thinsp;\u0026plusmn;\u0026thinsp;32.77 respectively. Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD protein intake of male and female was 23.22\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34and 22.66\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12 whereas mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD fat intake was 4.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31 and 4.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.48 respectively. In case of unhealthy diet like fatty rich food, empty caloric drink, street food, junk food and lack of fruit intake history did not find among the respondents. Table \u003cspan class=\"InternalRef\"\u003eA3\u003c/span\u003e in the appendix shows that soyabean oil intake among male and female was 68.5% and 71.2%, whereas mustard oil consumption was 31.5% and 28.8%, respectively whereas, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD oil intake was 2.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27 and 2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32 respectively. The mean energy expenditure of male and female was 1965.66 and 1633.44 and it was strongly significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Males (76.1%) were more active than females (69.8%).\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD body mass index (BMI) of respondents was 20.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56. More than half of the respondent (55.5%) was normal in terms of BMI whereas underweight and obesity was 32.6% and 11.8% respectively. Mean waist hip ratio was 0.92 and almost all of them was normal. (Table \u003cspan class=\"InternalRef\"\u003eA4\u003c/span\u003e in the appendix)\u003c/p\u003e\n \u003cp\u003eThe mean (\u0026plusmn;\u0026thinsp;SD) systolic blood pressure status of male and female was 109.26 (\u0026plusmn;\u0026thinsp;12.07) and 110.59 (\u0026plusmn;\u0026thinsp;38.35) respectively whereas diastolic blood pressure was 70.49 (\u0026plusmn;\u0026thinsp;10.44) and 70.25 (\u0026plusmn;\u0026thinsp;10.41) respectively. Most of the respondents both male and female had normal fasting blood glucose level. Mean (\u0026plusmn;\u0026thinsp;SD) fasting blood glucose level among male and female was 4.48 (\u0026plusmn;\u0026thinsp;0.734) and 4.46 (\u0026plusmn;\u0026thinsp;0.755) mmol/L respectively. In case of oral glucose tolerance test (OGTT) test, most of the respondents found normal in terms of blood glucose level but IGT was 3.3% among male and 13.8% among female. Mean (\u0026plusmn;\u0026thinsp;SD) of blood glucose among male and female was found 6.524 (\u0026plusmn;\u0026thinsp;1.133) and 6.675 (\u0026plusmn;\u0026thinsp;1.035) mmol/L respectively. Desirable and borderline cholesterol among male was 87.2% and 11.2% whereas 86.4% and 10.2% among female but high cholesterol was very low. Regarding HDL levels both male (80.8%) and female (76.2%) had high HDL but low HDL was negligible. Optimal, above optimal and borderline high LDL level among male and female was 41.6%, 34.4%, 20% and 46.3%, 29.3%, 18.4% respectively. In case of triglyceride most of male (89.6%) and female (87.8%) had normal level of triglyceride but high was minimal (Table \u003cspan class=\"InternalRef\"\u003eA5\u003c/span\u003e in the appendix).\u003c/p\u003e\n \u003cp\u003eMost of the respondents (95%) had normal blood pressure and rest 5% were hypertensive. Among them, 88.40% respondents had normal systolic blood pressure followed by pre-hypertension (8%), hypertension stage 1 (2.10%) and hypertension stage 2 (1.50%). In addition, 91.50% respondents had normal diastolic blood pressure followed by pre-hypertension (2.3%), hypertension stage 1 (4.60%) and hypertension stage 2 (1.50%).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eEconometric estimation\u003c/h3\u003e\n\u003cp\u003eThe econometric results involve systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, and BMI models (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All variables are assumed to follow a normal distribution. We evaluated the Log-likelihood (LL), Pseudo R-square, and Akaike information criterion (AIC) to assess model fit. A Log-likelihood value closer to zero indicates a decent model fit for choice experiment analysis. A Pseudo R-square greater than 0.20 suggests a well-fitted model. On the other hand, the smallest value of AIC indicates the best fitted model.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eResults of estimated regression models for NCDs\u003c/div\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1739799587.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eN.B.\u0026nbsp;\u003c/em\u003eStandard errors in parenthesis, \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSource:\u003c/strong\u003e Authors\u0026rsquo; calculation based on survey data, 2021\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003eSignificant association is found between age and systolic blood pressure. Likewise, there is statistically significant association between age and diastolic blood pressure, education and diastolic blood pressure, and monthly income and diastolic blood pressure. Religion has a great contribution to fasting blood glucose. On the other hand, martial status and monthly income are significant contributor to triglycerides, and education is a statistically influential factor of BMI. Positive sign of these variables (such as age, education, monthly income, and religion) is positively associated with few NCDs. According to [12] a standard Pseudo R-square takes the value ranging from 0.20\u0026ndash;0.30. In this viewpoint, all of our NCDs model are decent.\u003c/div\u003e\n"},{"header":"Discussion","content":"\u003cp\u003eThe current study indicated that most of the respondents (95%) had normal blood pressure and rest 5% had hypertensive. A population-based study done in the beginning of the decade found similar prevalence of hypertension (13%) [13], which was supportive to another population study in Bangladesh (12%) [14]. Recent studies done in rural community also suggested similar percentage [15]. Hypertension is a disease of its own as well as a risk factor for other major disease such as stroke, coronary heart disease, heart failure and renal insufficiency. It is very common in Bangladeshi people but its detection and treatment status are far from adequate. We should have intensive programme for salt reduction because its consumption is very high in the country. Estimated per capita salt intake based on salt production was 15.3 gm per day in 2001 [16], which is three times than a person requires for physiological functions of the body. This might be an important reason of high prevalence of hypertension in Bangladesh. A previous behavioral risk factor survey of NCDs in Bangladesh observed higher prevalence of table salt intake in both rural and urban areas. In rural area it was 92% and in urban area it was 46.3% [2]. Current study found that more than 50% of the study population took extra salt in term of table salt regularly which is a risk factor of high blood pressure.\u003c/p\u003e \u003cp\u003ePeople in Bangladesh usually do not measure blood glucose level. 83% of the survey population never measured their blood glucose. Considering the prevalence of diabetes among those who measured blood glucose was 3.9%. In men the percentage is slightly high. Population data in Bangladesh indicate an increasing trend in diabetes prevalence especially in urban areas. A higher prevalence of diabetes mellitus in the urban population was also observed compared with rural subjects by another population-based study [17]. There are lines of evidences that the prevalence of diabetes is rising in Bangladesh [18]. In urban area the prevalence is just double (10%) [19]. But present study showed that most of the respondents both male and female had normal fasting blood glucose level. Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD fasting blood glucose level among male and female was 4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.734 and 4.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.755 mmol/L, respectively. In case of OGTT test, most of the respondents found normal in terms of blood glucose level. Possible explanation for this may be their primitive lifestyle.\u003c/p\u003e \u003cp\u003eDesirable and borderline cholesterol among male was 87.2% and 11.2% whereas 86.4% and 10.2% among female but high cholesterol was very low. Regarding HDL level both male (80.8%) and female (76.2%) had high HDL but low HDL was negligible. Optimal, above optimal and borderline high LDL level among male and female was 41.6%, 34.4%, 20%, and 46.3%, 29.3%, 18.4%, respectively. In case of triglyceride most of male (89.6%) and female (87.8%) had normal level of triglyceride but high was minimal. A study observed sub-optimal cholesterol level in over half of the sample and overall, the mean serum cholesterol levels in their sample were comparable to that in the United States [20]. Mean levels of HDL cholesterol and triglycerides were lower than in the United States. Consistent with the comparison of the mean levels, the prevalence of low HDL cholesterol was higher but the prevalence of high triglyceride levels lower than in the United States [21].\u003c/p\u003e \u003cp\u003eObesity is believed by a section of the society to be a positive attribute, an indicator of a person's good health and prosperity. Evidence suggests that, in Bangladesh obesity is still not widely considered to be a health risk factor and in fact the converse, that losing weight is an indicator of illness, is more likely to be believed. This indicates that raising public awareness about the harmful consequences of obesity is necessary in order to influence societal norms concerning body size. Prevention and management of obesity are major challenges, especially in developing countries, where obesity often coexists with underweight. More than half of the respondents (55.5%) were normal in terms of BMI whereas underweight and overweight were 32.6% and 11.8% respectively whereas the national survey on NCD risk factors showed that one fourth of the population were underweight, 57% were normal and 18% were overweight. Similar findings were seen among several studies in Kuwait [22] and Saudi Arabia [23]. Actually, most of santal adibasis both men and women are hard worker and this tendency leads them to prevent overweight and obesity.\u003c/p\u003e \u003cp\u003eWaist circumference provides an indication about the central obesity and has been suggested to be a risk factor more specific to cardiovascular disease as visceral fat is considered as a predictor of morbidity and mortality. This alone provides similar information as waist-hip ratio. Like general obesity the central obesity was also more in women. Overall, one in five had increased waist circumference. Recently waist circumference has been implicated with individual's propensity to develop NCDs. Higher prevalence of central and general adiposity in women indicates that women may be at a relatively increased risk of cardiovascular disease.\u003c/p\u003e \u003cp\u003eSmoking habit was statistically significant in terms of smoking status, types of smoking, number of sticks consumed per day and smokeless tobacco. Almost half of the respondents had the habit of current smoking (45.2%) whereas NCD risk factor survey in Bangladesh found that the overall prevalence of smoking was 26.2%. From the data, we can see that prevalence of smoking is much higher in the study population. Smoking is clearly a major threat for health. A recent study conducted by [24] found that 41% of the eight killer diseases (heart attack, stroke, oral cancer, larynx cancer, lung cancer, Berger\u0026rsquo;s disease, tuberculosis and chronic obstructive pulmonary disease) are attributable to tobacco usage. Another study revealed that prevalence rate of daily smoking of 7.2% with variations among age, sex, religion and regions which findings were very much lower to current study [25].\u003c/p\u003e \u003cp\u003eThough consumption of alcohol is low in Bangladesh, due to sociocultural inhibition but this is quite ignored among ethnic communities because their sociocultural practice is different from Bengali people. The present study found that current alcohol drinker was more among male (53.3%) but never drinker was prominent among female (57.6%) and occasional drinker was quite similar in both males and females which was similar to the cross-sectional survey conducted among all the ethnic groups in Ethiopia with the WHO STEP wise approach [26]. This survey, therefore, identified large number of people with behavioral risk factors for NCDs that require immediate interventions and longer-term monitoring as a priority measure in Bangladesh. The prevalence of low physical activity was 27.2% among the study population whereas 27% of the mainstream population found to be in the low physical activity category. It shows that almost similar findings in case of physical inactivity.\u003c/p\u003e \u003cp\u003eMean age of the respondents was estimated at 38.05 years and [27] showed that mean age was 42.4 years which was quite similar with present study. Most of the participants were married. More than half (53%) of the respondents were farmer. [27] further reported in men farmers made up 22.8%, 19.2% were small businessmen, 12% were day laborer and 11.8% nongovernment employee. In women, housewives made up 83.4% of the surveyed population.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNCDs pose a significant global health burden. However, the prevalence and risk factors of NCDs among specific populations, such as \u003cem\u003eSantal Adivasis\u003c/em\u003e, remain understudied. This study aims to summarize existing evidence on NCD risk factors in this population and highlight areas for further investigation. NCDs, including hypertension, diabetes, dyslipidemia, and obesity, contribute substantially to morbidity and mortality worldwide. Santal Adivasis, an indigenous community, exhibit unique health profiles. While shared immediate risk factors for NCDs are notably low among Santal Adivasis, there is a concerning prevalence of underweight individuals. The impact of underweight on NCD outcomes requires further exploration.\u003c/p\u003e \u003cp\u003eThe use of tobacco, particularly from early adulthood, emerges as a major risk factor for CVDs in \u003cem\u003eSantal Adivasis\u003c/em\u003e, especially among males. Similar to tobacco, alcohol misuse contributes significantly to CVD risk in this population. Rather than the typical problem of positive energy balance seen in other populations, \u003cem\u003eSantal Adivasis\u003c/em\u003e face undernutrition as a predominant dietary issue. Investigating its impact on NCDs is crucial. Understanding dietary patterns and food choices specific to this community is essential. As age increases, the prevalence of shared NCD risk factors rises. This trend warrants attention in preventive strategies. \u003cem\u003eSantal\u003c/em\u003e males are more vulnerable to behavioral risk factors (e.g., smoking, alcohol consumption. Whereas, a higher proportion of \u003cem\u003eSanta\u003c/em\u003el females suffer from IGT, an important NCD risk factor.\u003c/p\u003e \u003cp\u003eFurther research is needed to comprehensively assess NCD prevalence, risk factors, and outcomes among Santal Adivasis. Policymakers and health practitioners should consider these findings to tailor interventions effectively.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSD\u003c/em\u003e:\u0026nbsp;\u003c/strong\u003eStandard deviation\u003c/p\u003e\n\u003cp\u003eSPSS: Statistical package for the social sciences\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors express their sincere gratitude to the anonymous reviewers for their valuable comments and suggestions. They also extend their appreciation to all respondents for generously providing insightful data and information, which significantly contributed to the successful completion of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBangladesh University of Health Science, Dhaka 1216, Bangladesh\u003c/p\u003e\n\u003cp\u003eSharmin Sultana\u003c/p\u003e\n\u003cp\u003eTel.: +66(0) 91-704-3684; E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003eORCID ID: 0009-0003-6236-7860\u003c/p\u003e\n\u003cp\u003eGovernment Edward College, Pabna 6600, Bangladesh\u003c/p\u003e\n\u003cp\u003eMd. Hafiz Iqbal, PhD\u003c/p\u003e\n\u003cp\u003eTel.: +880-1717-278232; +880-1776-196953; E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003eORCID: 0000-0001-6181-1980\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSS:\u003c/strong\u003e Conceptualization, Methodology, Software, Data curation, Formal Analysis, and Original draft preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMHI:\u003c/strong\u003e Validation, Visualization, Investigation, Visualization, Supervision, review and editing\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author(s)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to\u0026nbsp;Sharmin Sultana and Md. Hafiz Iqbal\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Bangladesh University of Health Science (BUHS) Research Ethics Committee (Reference number:\u0026nbsp;BUHS/ERC/EA/23/388). Ethical standards outlined in the Declaration of Helsinki and its subsequent amendments were followed, ensuring confidentiality and voluntary participation. All participants provided informed consent before the survey, and were free to withdraw at any time without explanation. To guarantee anonymity, no personal identifiers were collected, and all responses remained confidential. Participants confirmed their consent by checking a box indicating they had read, understood, and agreed to the terms of participation. Contact details for the researchers were provided for any inquiries.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests related to the research, authorship, and/or publication of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRahman SA, Kielmann T, McPake B, Normand C. Healthcare-seeking behaviour among the tribal people of Bangladesh: can the current health system really meet their needs? Journal of Health, Population, and Nutrition. 2012; 30(3): 353. Available from: https://doi.org/ 10.3329/jhpn.v30i3.12299\u003c/li\u003e\n\u003cli\u003eIslam MF. Cultural Change and Adaptation of Munda Tribe of Bangladesh: A Socio-Anthropological Analysis. Indian Journal of Anthropological Research. 2023; \u003cem\u003e2\u003c/em\u003e(2):139-156. 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BMJ Open. 2020; 10(11): e041334. https://doi.org/ doi:10.1136/bmjopen-2020-041334\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Non-communicable diseases, Modifiable intermediate risk factors, Socio-demographic-anthropometric factors, Behavioral risk factor, Ethnic minorities","lastPublishedDoi":"10.21203/rs.3.rs-6002058/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6002058/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThere is increasing evidence that rate of non-communicable diseases (NCDs) vary among different groups. However, studies related to disease burden and its risk factors among ethnic minorities are rare in Bangladesh. To fill this gap, our study explores the prevalence of various risk factors for major NCDs among \u003cem\u003eSantal Adivasis\u003c/em\u003e and compares the interrelationship among different groups of risk factors.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEmploying purposive sampling techniques, data were collected from 389 respondents in Birgonj \u003cem\u003eUpazila\u003c/em\u003e of Dinajpur district through a pretested questionnaire. In addition to socio-demographic-anthropometric factors, laboratory diagnoses were conducted following standard techniques. Data were analyzed using univariate regression analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe prevalence of shared immediate risk factors for NCDs is remarkably low among \u003cem\u003eSantal Adivasis\u003c/em\u003e. Among the modifiable intermediate risk factors, the use of tobacco and harmful alcohol consumption from early adulthood poses major risks for cardiovascular diseases in this population. Males appear to be more vulnerable to behavioral risk factors such as smoking and alcohol consumption, while a significantly higher proportion of females suffer from impaired glucose tolerance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclution\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe findings of this study emphasize the importance of targeted policies and interventions to improve health outcomes in this ethnic minority group.\u003c/p\u003e","manuscriptTitle":"Addressing risk factors of Santals Adivasis: Policy recommendations for non-communicable diseases in Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-17 13:49:21","doi":"10.21203/rs.3.rs-6002058/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"da452779-a212-4499-95f6-ee80d4e4f6a5","owner":[],"postedDate":"February 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-25T09:23:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-17 13:49:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6002058","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6002058","identity":"rs-6002058","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}