FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4309227918> ?p ?o ?g. }

• W4309227918 abstract "Abstract Background Cardiovascular diseases (CVDs) are the leading cause of death in most low- and middle-income countries (LMICs). CVDs and their metabolic risk factors have historically been concentrated among urban residents with higher socioeconomic status (SES) in LMICs such as India. However, as India develops, it is unclear whether these socioeconomic and geographic gradients will persist or change. Understanding these social dynamics in CVD risk is essential for mitigating the rising burden of CVDs and to reach those with the greatest needs. Methods Using nationally representative data with biomarker measurements from the fourth (2015-16) and fifth (2019-21) Indian National Family and Health Surveys, we investigated trends in the prevalence of four CVD risk factors: tobacco consumption (self-reported, any type), unhealthy weight , idiabetes (random plasma glucose concentration ≥200mg/dL or self-reported diabetes), and hypertension (one of: average systolic blood pressure ≥ 140mmHg, average diastolic blood pressure ≥ 90mmHg, self-reported past diagnosis, or self-reported current antihypertensive medication use) among adults aged 15-49 years. We first described changes at the national level and then trends stratified by place of residence (urban versus rural), geographic region (northern, northeastern, central, eastern, western, southern), regional level of development (Empowered Action Group member state or not), and two measures of socioeconomic status: level of education (no education, primary incomplete, primary complete, secondary incomplete, secondary complete, higher) and wealth (quintiles). Findings Unhealthy weight increased among all social and geographic groups but both the absolute and the relative changes were substantially higher among people with low SES (as measured by education or wealth) and in rural areas. For diabetes and hypertension, the prevalence increased for those from disadvantaged groups while staying constant or even decreasing among the wealthier and more educated. In contrast, tobacco consumption declined for all social and geographic groups. Interpretation In 2015-16, CVD risk factors were higher among more advantaged subpopulations in India. However, between 2015-16 and 2019-21, the prevalence of these risk factors grew more rapidly for less wealthy and less educated subpopulations and those living in rural areas. These trends have resulted in CVD risk becoming far more widespread throughout the population; CVD can no longer be characterized as a wealthy urban phenomenon. Funding This work was supported by the Alexander von Humboldt Foundation [NS]; the Stanford Diabetes Research Center [PG], and the Chan Zuckerberg Biohub [PG]. Research in Context Evidence before this study We searched PubMed for work published between Jan 1, 1990, and Sep 23, 2022, with variations of the search terms “reversal hypothesis”, “social gradient”, “socioeconomic gradient”, “social difference”, “socioeconomic difference”, “socioeconomic status”, “change”, “trend”, “cardiovascular disease”, “cardiovascular risk factor”, “diabetes”, “hypertension”, “overweight”, “obesity”, “smoking”, “tobacco”, “low-income”, “lower-middle-income”, and “India” in the title or abstract. Existing studies on changes in the socioeconomic patterning of cardiovascular disease (CVD) risk factors mostly compared the size of social gradients in obesity cross-sectionally between countries at different levels of national income or development. These studies generally found higher obesity among higher socioeconomic status (SES) populations but opposite gradients for countries at higher levels of development. However, because these studies use cross-sectional comparisons, whether these patterns reflect the influence of development or other contextual factors associated with countries at different levels of development is unclear. Both for obesity and for other CVD risk factors, we found few nationally-representative studies that traced how gradients within countries changed over time as they developed. Importantly, most of these studies did not focus on India and those that did only considered single risk factors such as obesity using older data. Existing nationally representative research on India is thus predominantly cross-sectional and has only focused on the size of social gradients at single points in time. This work generally finds higher levels of unhealthy weight, diabetes, and hypertension among wealthy and educated subpopulations but lower levels of tobacco consumption. Subnational and smaller non-representative studies from India that traced changes in CVD risk factors over time provide some evidence of reversing or flattening gradients but it is unclear whether these patterns hold at regional and national levels. Added value of this study Using data from the 2015-16 and 2019-2021 National Family and Health Surveys, we provide some of the first nationally representative evidence for trends in the prevalence of major CVD risk factors in India and how these trends have changed across social and geographic groups. Both absolute and relative increases in prevalence were far more pronounced among relatively poor and less educated populations. As a result of these trends, most CVD risk factors became more equal across population groups, or in some cases, became higher among the less compared to more educated. Implications of all the available evidence Indians with lower SES – as measured by wealth and education – experienced considerable adverse trends in unhealthy weight, diabetes, and hypertension between 2015-16 and 2019-21. Our results reveal that CVDs can no longer be considered a problem of the affluent parts of society and suggest that CVD prevention efforts that reach less advantaged subpopulations are urgently needed." @default.
• W4309227918 created "2022-11-24" @default.
• W4309227918 creator A5015160949 @default.
• W4309227918 creator A5017362281 @default.
• W4309227918 creator A5018621533 @default.
• W4309227918 creator A5039559852 @default.
• W4309227918 creator A5045397336 @default.
• W4309227918 creator A5047552667 @default.
• W4309227918 creator A5050649371 @default.
• W4309227918 creator A5084515555 @default.
• W4309227918 creator A5091452650 @default.
• W4309227918 date "2022-11-13" @default.
• W4309227918 modified "2023-10-10" @default.
• W4309227918 title "Changing socioeconomic and geographic gradients in cardiovascular disease risk factors in India – Evidence from nationally representative household surveys" @default.
• W4309227918 cites W1772715720 @default.
• W4309227918 cites W1900956557 @default.
• W4309227918 cites W2022757173 @default.
• W4309227918 cites W2069787702 @default.
• W4309227918 cites W2095545012 @default.
• W4309227918 cites W2103497017 @default.
• W4309227918 cites W2135515058 @default.
• W4309227918 cites W2145604887 @default.
• W4309227918 cites W2149159105 @default.
• W4309227918 cites W2153630285 @default.
• W4309227918 cites W2159430955 @default.
• W4309227918 cites W2162651972 @default.
• W4309227918 cites W2165150824 @default.
• W4309227918 cites W2194955989 @default.
• W4309227918 cites W2335807471 @default.
• W4309227918 cites W2586747580 @default.
• W4309227918 cites W2587673737 @default.
• W4309227918 cites W2618022510 @default.
• W4309227918 cites W2621734556 @default.
• W4309227918 cites W2760211785 @default.
• W4309227918 cites W2795707819 @default.
• W4309227918 cites W2803065068 @default.
• W4309227918 cites W2893552430 @default.
• W4309227918 cites W2896879923 @default.
• W4309227918 cites W2931736217 @default.
• W4309227918 cites W2947599255 @default.
• W4309227918 cites W2970958862 @default.
• W4309227918 cites W3014402135 @default.
• W4309227918 cites W3042446616 @default.
• W4309227918 cites W3081065055 @default.
• W4309227918 cites W3130044647 @default.
• W4309227918 cites W3156062736 @default.
• W4309227918 cites W3162704165 @default.
• W4309227918 cites W4205151565 @default.
• W4309227918 cites W4220814054 @default.
• W4309227918 cites W4280608319 @default.
• W4309227918 doi "https://doi.org/10.1101/2022.11.11.22282234" @default.
• W4309227918 hasPublicationYear "2022" @default.
• W4309227918 type Work @default.
• W4309227918 citedByCount "1" @default.
• W4309227918 countsByYear W43092279182023 @default.
• W4309227918 crossrefType "posted-content" @default.
• W4309227918 hasAuthorship W4309227918A5015160949 @default.
• W4309227918 hasAuthorship W4309227918A5017362281 @default.
• W4309227918 hasAuthorship W4309227918A5018621533 @default.
• W4309227918 hasAuthorship W4309227918A5039559852 @default.
• W4309227918 hasAuthorship W4309227918A5045397336 @default.
• W4309227918 hasAuthorship W4309227918A5047552667 @default.
• W4309227918 hasAuthorship W4309227918A5050649371 @default.
• W4309227918 hasAuthorship W4309227918A5084515555 @default.
• W4309227918 hasAuthorship W4309227918A5091452650 @default.
• W4309227918 hasBestOaLocation W43092279181 @default.
• W4309227918 hasConcept C126322002 @default.
• W4309227918 hasConcept C134018914 @default.
• W4309227918 hasConcept C144024400 @default.
• W4309227918 hasConcept C147077947 @default.
• W4309227918 hasConcept C149923435 @default.
• W4309227918 hasConcept C205649164 @default.
• W4309227918 hasConcept C2776269092 @default.
• W4309227918 hasConcept C2779134260 @default.
• W4309227918 hasConcept C2908647359 @default.
• W4309227918 hasConcept C555293320 @default.
• W4309227918 hasConcept C71924100 @default.
• W4309227918 hasConcept C84393581 @default.
• W4309227918 hasConcept C99454951 @default.
• W4309227918 hasConceptScore W4309227918C126322002 @default.
• W4309227918 hasConceptScore W4309227918C134018914 @default.
• W4309227918 hasConceptScore W4309227918C144024400 @default.
• W4309227918 hasConceptScore W4309227918C147077947 @default.
• W4309227918 hasConceptScore W4309227918C149923435 @default.
• W4309227918 hasConceptScore W4309227918C205649164 @default.
• W4309227918 hasConceptScore W4309227918C2776269092 @default.
• W4309227918 hasConceptScore W4309227918C2779134260 @default.
• W4309227918 hasConceptScore W4309227918C2908647359 @default.
• W4309227918 hasConceptScore W4309227918C555293320 @default.
• W4309227918 hasConceptScore W4309227918C71924100 @default.
• W4309227918 hasConceptScore W4309227918C84393581 @default.
• W4309227918 hasConceptScore W4309227918C99454951 @default.
• W4309227918 hasLocation W43092279181 @default.
• W4309227918 hasOpenAccess W4309227918 @default.
• W4309227918 hasPrimaryLocation W43092279181 @default.
• W4309227918 hasRelatedWork W1954094490 @default.
• W4309227918 hasRelatedWork W1987177400 @default.
• W4309227918 hasRelatedWork W2036744340 @default.
• W4309227918 hasRelatedWork W2044417549 @default.
• W4309227918 hasRelatedWork W2136236859 @default.

• next