Tobacco use as a risk factor of Non-Communicable Diseases among the migrants of Santal tribe in Bhubaneswar city, Odisha, India Article Swipe
Himanshu Sekhar Pradhan
,
Bagavandas Mappillairaju
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.70135/seejph.vi.3726
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.70135/seejph.vi.3726
Introduction:Migration and urbanization have a significant impact on the health and lifestyle of tribal populations in India. Risk factors for Non-Communicable Diseases (NCDs) are increasing and are frequently associated with the adoption of unhealthy lifestyles including tobacco and alcohol consumption, low physical activities and unhealthy dietary choices. Odisha, having a sizable tribal population, demonstrates considerable disparities in tobacco consumption, a known risk factor of NCDs, emphasizing the necessity for area-specific evidence to shape prevention strategies.Objective:To assess the prevalence, patterns, and factors associated with tobacco consumption as a behavioral risk factor for non-communicable diseases among adult Santal tribal migrants (18–69 years) living in Bhubaneswar city, Odisha.Methodology:A cross-sectional survey was performed from September to December 2022, by using adapted World Health Organization's STEPS survey questionnaire on surveillance of risk factors of non-communicable diseases. A total of 516 Santal migrant workers were chosen through a multi-stage sampling technique from slums throughout Bhubaneswar. Descriptive statistics were used to summarize data, chi-square tests examined associations, and logistic regression identified key predictors of tobacco use.Results:The prevalence of tobacco consumption among Santal migrants was 80% (95% CI: 76.3–83.3), higher in males compared to females (86% vs. 71.8%). Males primarily smoked (68.3%), while in both genders smokeless tobacco consumption was common (72.3% in males and 70.4% in females). Tobacco use was significantly associated with marital status, no formal education, and alcohol use. Tobacco use was higher among the age group of 45 to 69 years (88.1%) than among the younger age groups (75.8%).Conclusion:This study has found a very high prevalence of tobacco consumption among the migrants of Santal tribe in Bhubaneswar, Odisha. The results highlight the need for focused public health interventions to reduce the risk factor of non-communicable diseases among urban tribal populations.
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- en
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- OA Status
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4407322536Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.70135/seejph.vi.3726Digital Object Identifier
- Title
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Tobacco use as a risk factor of Non-Communicable Diseases among the migrants of Santal tribe in Bhubaneswar city, Odisha, IndiaWork title
- Type
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-01-20Full publication date if available
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Himanshu Sekhar Pradhan, Bagavandas MappillairajuList of authors in order
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https://doi.org/10.70135/seejph.vi.3726Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.70135/seejph.vi.3726Direct OA link when available
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Tribe, Migrant workers, Tobacco use, Socioeconomics, Geography, Risk factor, Environmental health, Non-communicable disease, Medicine, Traditional medicine, Sociology, Public health, Economic growth, Anthropology, Economics, Nursing, Population, Internal medicineTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.status, | 217 |
| abstract_inverted_index.through | 140 |
| abstract_inverted_index.tobacco | 36, 57, 83, 167, 171, 199, 253 |
| abstract_inverted_index.workers | 137 |
| abstract_inverted_index.younger | 241 |
| abstract_inverted_index.(18–69 | 98 |
| abstract_inverted_index.(68.3%), | 193 |
| abstract_inverted_index.December | 112 |
| abstract_inverted_index.Diseases | 21 |
| abstract_inverted_index.adoption | 31 |
| abstract_inverted_index.choices. | 46 |
| abstract_inverted_index.compared | 184 |
| abstract_inverted_index.diseases | 92, 281 |
| abstract_inverted_index.evidence | 70 |
| abstract_inverted_index.examined | 158 |
| abstract_inverted_index.logistic | 161 |
| abstract_inverted_index.migrants | 97, 175, 257 |
| abstract_inverted_index.physical | 41 |
| abstract_inverted_index.sampling | 143 |
| abstract_inverted_index.September | 110 |
| abstract_inverted_index.diseases. | 130 |
| abstract_inverted_index.females). | 209 |
| abstract_inverted_index.highlight | 266 |
| abstract_inverted_index.including | 35 |
| abstract_inverted_index.lifestyle | 11 |
| abstract_inverted_index.necessity | 67 |
| abstract_inverted_index.patterns, | 78 |
| abstract_inverted_index.performed | 108 |
| abstract_inverted_index.primarily | 191 |
| abstract_inverted_index.smokeless | 198 |
| abstract_inverted_index.summarize | 154 |
| abstract_inverted_index.technique | 144 |
| abstract_inverted_index.unhealthy | 33, 44 |
| abstract_inverted_index.activities | 42 |
| abstract_inverted_index.associated | 28, 81, 214 |
| abstract_inverted_index.behavioral | 87 |
| abstract_inverted_index.chi-square | 156 |
| abstract_inverted_index.education, | 220 |
| abstract_inverted_index.frequently | 27 |
| abstract_inverted_index.identified | 163 |
| abstract_inverted_index.increasing | 24 |
| abstract_inverted_index.lifestyles | 34 |
| abstract_inverted_index.predictors | 165 |
| abstract_inverted_index.prevalence | 169, 251 |
| abstract_inverted_index.prevention | 73 |
| abstract_inverted_index.regression | 162 |
| abstract_inverted_index.statistics | 150 |
| abstract_inverted_index.throughout | 147 |
| abstract_inverted_index.Bhubaneswar | 102 |
| abstract_inverted_index.Descriptive | 149 |
| abstract_inverted_index.consumption | 84, 172, 200, 254 |
| abstract_inverted_index.disparities | 55 |
| abstract_inverted_index.emphasizing | 65 |
| abstract_inverted_index.multi-stage | 142 |
| abstract_inverted_index.population, | 52 |
| abstract_inverted_index.populations | 14 |
| abstract_inverted_index.prevalence, | 77 |
| abstract_inverted_index.significant | 5 |
| abstract_inverted_index.Bhubaneswar, | 262 |
| abstract_inverted_index.Bhubaneswar. | 148 |
| abstract_inverted_index.considerable | 54 |
| abstract_inverted_index.consumption, | 39, 58 |
| abstract_inverted_index.demonstrates | 53 |
| abstract_inverted_index.populations. | 285 |
| abstract_inverted_index.surveillance | 124 |
| abstract_inverted_index.urbanization | 2 |
| abstract_inverted_index.76.3–83.3), | 180 |
| abstract_inverted_index.area-specific | 69 |
| abstract_inverted_index.associations, | 159 |
| abstract_inverted_index.interventions | 273 |
| abstract_inverted_index.questionnaire | 122 |
| abstract_inverted_index.significantly | 213 |
| abstract_inverted_index.Organization's | 119 |
| abstract_inverted_index.cross-sectional | 105 |
| abstract_inverted_index.use.Results:The | 168 |
| abstract_inverted_index.Non-Communicable | 20 |
| abstract_inverted_index.non-communicable | 91, 129, 280 |
| abstract_inverted_index.Odisha.Methodology:A | 104 |
| abstract_inverted_index.Introduction:Migration | 0 |
| abstract_inverted_index.(75.8%).Conclusion:This | 244 |
| abstract_inverted_index.strategies.Objective:To | 74 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.04721979 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |