Interaction of multiple risk factors and population attributable fraction for type 2 diabetes and hypertension among adults aged 15–49 years in Northeast India

Marbaniang, Strong P.; Lhungdim, Hemkhothang; Chauhan, Shekhar

doi:10.1016/j.dsx.2021.102227

Cited by 12 publications

(10 citation statements)

References 41 publications

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“…Therefore, it is considered that a person's higher level of education serves as a safety net for them and lowers their risk of contracting communicable diseases. Since educated people are more likely to be wealthy and have sedentary lifestyles, which increase their risk of non-communicable illness, they have higher probabilities of developing NCD [ 27 – 29 ].…”

Section: Discussionmentioning

confidence: 99%

Burden of communicable and non-communicable diseases-related inequalities among older adults in India: a study based on LASI survey

et al. 2022

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Background A rising proportion of elderly in India has infused notable challenges to the healthcare system, which is already underdeveloped. On one side, NCDs are increasing among the elderly in India; however, on the other side, CDs are also a cause of concern among the elderly in India. While controlling the outbreak of communicable diseases (CDs) remained a priority, non-communicable diseases (NCDs) are placing an unavoidable burden on the health and social security system. India, a developing nation in South Asia, has seen an unprecedented economic growth in the past few years; however, it struggled to fight the burden of communicable and non-communicable diseases. Therefore, this study aimed at examining the burden of CDs and NCDs among elderly in India. Methods Data from Longitudinal Ageing Study in India (LASI Wave-I, 2017–18) were drawn to conduct this study. The LASI is a large-scale nationwide scientific study of the health, economics, and social determinants and implications of India's aged population. The LASI is a nationally representative survey of 72,250 aged 45 and over from all Indian states and union territories. Response variables were the occurrence of CDs and NCDs. The bi-variate and binary logistic regression were used to predict the association between communicable and non-communicable diseases by various socio-demographic and health parameters. Furthermore, to understand the inequalities of communicable and non-communicable diseases in urban and rural areas, the Fairlie decomposition technique was used to predict the contribution toward rural–urban inequalities in CDs and NCDs. Results Prevalence of communicable diseases was higher among uneducated elderly than those with higher education (31.9% vs. 17.3%); however, the prevalence of non-communicable diseases was higher among those with higher education (67.4% vs. 47.1%) than uneducated elderly. The odds of NCDs were higher among female elderly (OR = 1.13; C.I. = 1–1.27) than their male counterparts. Similarly, the odds of CDs were lower among urban elderly (OR = 0.70; C.I. = 0.62–0.81) than rural elderly, and odds of NCDs were higher among urban elderly (OR = 1.85; C.I. = 1.62–2.10) than their rural counterparts. Results found that education (50%) contributes nearly half of the rural–urban inequality in the prevalence of CDs among the elderly. Education status and current working status were the two significant predictors of widening rural–urban inequality in the prevalence of NCDs among the elderly. Conclusion The burden of both CD and NCD among the elderly population requires immediate intervention. The needs of men and women and urban and rural elderly must be addressed through appropriate efforts. In a developing country like India, preventive measures, rather than curative measures of communicable diseases, will be cost-effective and helpful. Further, focusing on educational interventions among older adults might bring some required changes.

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Section: Discussionmentioning

confidence: 99%

Burden of communicable and non-communicable diseases-related inequalities among older adults in India: a study based on LASI survey

et al. 2022

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“…Previous studies have shown that socioeconomic factors–such as low levels of education, high household economic status, and demographic factors like age and sex–increase the risk of diabetes and hypertension [ 10 , 11 ]. Lifestyle behaviours like smoking, alcohol consumption [ 11 – 13 ], low physical activity [ 14 ], and dietary habits [ 15 , 16 ] also significantly influence the risk of diabetes and hypertension. Individuals in the same geographical area usually have common beliefs and culture, which may lead to similar levels of exposure to diseases, including diabetes and hypertension [ 17 – 19 ].…”

Section: Introductionmentioning

confidence: 99%

A structured additive modeling of diabetes and hypertension in Northeast India

2022

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Background Multiple factors are associated with the risk of diabetes and hypertension. In India, they vary widely even from one district to another. Therefore, strategies for controlling diabetes and hypertension should appropriately address local risk factors and take into account the specific causes of the prevalence of diabetes and hypertension at sub-population levels and in specific settings. This paper examines the demographic and socioeconomic risk factors as well as the spatial disparity of diabetes and hypertension among adults aged 15–49 years in Northeast India. Methods The study used data from the Indian Demographic Health Survey, which was conducted across the country between 2015 and 2016. All men and women between the ages of 15 and 49 years were tested for diabetes and hypertension as part of the survey. A Bayesian geo-additive model was used to determine the risk factors of diabetes and hypertension. Results The prevalence rates of diabetes and hypertension in Northeast India were, respectively, 6.38% and 16.21%. The prevalence was higher among males, urban residents, and those who were widowed/divorced/separated. The functional relationship between household wealth index and diabetes and hypertension was found to be an inverted U-shape. As the household wealth status increased, its effect on diabetes also increased. However, interestingly, the inverse was observed in the case of hypertension, that is, as the household wealth status increased, its effect on hypertension decreased. The unstructured spatial variation in diabetes was mainly due to the unobserved risk factors present within a district that were not related to the nearby districts, while for hypertension, the structured spatial variation was due to the unobserved factors that were related to the nearby districts. Conclusion Diabetes and hypertension control measures should consider both local and non-local factors that contribute to the spatial heterogeneity. More importance should be given to efforts aimed at evaluating district-specific factors in the prevalence of diabetes within a region.

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“…An association between consumption of aerated drinks and HT among adults has been noted amongst Indian adults previously too. [ 29 ] Interestingly, it was observed that women consuming fried foods had about 15–20% lower odds of developing HT.…”

Section: Discussionmentioning

confidence: 99%

Urban–rural disparities in blood pressure and lifestyle risk factors of hypertension among Indian individuals

Venkatesh

Grover

Vignitha

et al. 2022

Journal of Family Medicine and Primary Care

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Objectives: This study aims to assess the urban–rural difference in prevalence of hypertension (HT) and to explore the disparities in lifestyle risk factors of HT among urban and rural individuals aged 15–49 years in India. Study Design: The cross-sectional data collected as a part of the fourth round of National Family Health Survey (NFHS-4) was analysed in this observational study. NFHS-4 was conducted between January 2015 and December 2016 amongst men aged 15–54 years and women aged 15–49 years. In order to maintain uniformity, age group of 15–49 years was considered. Descriptive analyses were performed for sociodemographic and lifestyle factors. Binary logistic regression was conducted to assess the predictors of HT in men and women in urban and rural settings. The presence of HT was considered as the outcome variable. Results: The overall age adjusted prevalence of HT was 17.2% and was greater in urban (18.3%) than in rural population (15.5%). The age adjusted prevalence was also higher in males (18.2%) as compared to females (16.1%). Age and wealth were associated with HT in both urban and rural population. Education and dietary habits played a role in all except rural men. Alcohol consumption, diabetic status and marital status were significantly associated with HT in both urban and rural women. Occupation was associated with HT only in urban women. Conclusions: The study has shown higher HT prevalence in urban areas despite higher prevalence of lifestyle risk factors in rural settings. This calls for more robust screening and health education in the entire population, especially in rural areas.

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Interaction of multiple risk factors and population attributable fraction for type 2 diabetes and hypertension among adults aged 15–49 years in Northeast India

Cited by 12 publications

References 41 publications

Burden of communicable and non-communicable diseases-related inequalities among older adults in India: a study based on LASI survey

Burden of communicable and non-communicable diseases-related inequalities among older adults in India: a study based on LASI survey

A structured additive modeling of diabetes and hypertension in Northeast India

Urban–rural disparities in blood pressure and lifestyle risk factors of hypertension among Indian individuals

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