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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 18  |  Issue : 4  |  Page : 191-195

Factors affecting hypertension among rural geriatric population in Odisha: Findings from AHSETS study


1 Department of Community Medicine, SLN Medical College, Koraput, Odisha, India
2 Department of Surgery, PRM Medical College, Baripada, Odisha, India
3 Department of Public Health, ICMR-RMRC, Bhubaneswar, Odisha, India
4 Department of Health and Family Welfare, Ministry of Health and Family Welfare, New Delhi, India

Date of Submission05-Jul-2022
Date of Decision15-Sep-2022
Date of Acceptance09-Dec-2022
Date of Web Publication27-Dec-2022

Correspondence Address:
Dr. Trilochan Bhoi
Ministry of Health and Family Welfare, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jiag.jiag_32_22

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  Abstract 


Background: Worldwide, around 1.28 billion adults, aged 30–79 years have hypertension (HTN) and most (two-thirds) of them living in low- and middle-income countries like India. While only less than half of adults (42%) with HTN are diagnosed and treated. This study is an effort to estimate the prevalence and determine the determinants of HTN among the rural elderly population in Tigira block, Cuttack district of Odisha. Methodology: This cross-sectional study was carried out among 725 rural elderly (>60 years) people using probability proportionate to sample (PPS) sampling in the year 2019–2020. Previous medical history of HTN diagnosed by medical professional was taken as positive for HTN. Bivariate analysis was performed using the Chi-square test. The binary logistic regression model was used to find out the predictors of HTN. Results: This cross-sectional study found an HTN prevalence of 34.75% (n = 252) among rural older adults. Factors found to be significantly associated with HTN were female gender (adjusted odds ratio [AOR] = 1.73, confidence interval [CI] = 1.129–2.666), elderly aged ≥80 years (AOR = 1.98, CI = 1.170–3.379), not working elderly (AOR = 2.14, CI = 1.178–3.89), lower-middle socioeconomic status (SES) (AOR = 1.61, CI = 1.093–2.372), overweight elderly (AOR = 2.01, CI = 1.309–3.098) and diabetics (AOR = 4.56, CI = 2.704–7.718), respectively. Conclusion: HTN prevalence was found to be high in the rural area, and the factors such as female gender, elderly aged ≥80 years, not working elderly, lower-middle SES, overweight elderly, and diabetes were found to be the determinants of HTN in the rural elderly population of Odisha.

Keywords: Hypertension, Odisha, older adults, risk factors, rural


How to cite this article:
Biswal RK, Kumar Subudhi B S, Sethi S, Kshatri JS, Bhoi T. Factors affecting hypertension among rural geriatric population in Odisha: Findings from AHSETS study. J Indian Acad Geriatr 2022;18:191-5

How to cite this URL:
Biswal RK, Kumar Subudhi B S, Sethi S, Kshatri JS, Bhoi T. Factors affecting hypertension among rural geriatric population in Odisha: Findings from AHSETS study. J Indian Acad Geriatr [serial online] 2022 [cited 2023 Feb 8];18:191-5. Available from: http://www.jiag.com/text.asp?2022/18/4/191/365768




  Introduction Top


“National policy on older persons (1999),” define “elderly” as an individual with an age more than equal to 60 years.[1] Globally, people are living longer and all the countries experiencing population growth of older adults. The older adults' population will increase to 1.4 billion in 2030 from 1 billion in 2020 and one in every six people will be aged more than equal to 60 years. The population aged 60 years or above is likely to reach 2.1 billion and 80 years or above will be triple between 2020 and 2050. Currently, the lower and middle-income countries are experiencing the greatest shift in the country's population toward older ages or population aging, which was started in high-income countries. It was predicted that, by 2050, around 80% (two third) of the world's older adult population will be residing in LMIC like India.[2]

India is a rural-based country where 65% of the total population residing in rural areas and it is predicted that in 2050, the population will be equally distributed between rural and urban areas.[3],[4] Geriatric population contributes around 9% of the total population of Odisha, and 86.3% of them residing in rural areas where health facilities are poor. It is predicted that the elderly population in Odisha will increase from 8% in 2015 to 19% in 2050.[5]

The impact of the accumulation of different types of molecular and cellular damage with an increase in age results in aging. This leads to a gradual decrease in physical and mental capacity, a growing risk of disease, and ultimately death. These changes are neither linear nor consistent, and they are only loosely associated with a person's age in years.[2] Among the rural elderly people, the common disorders found are such as musculoskeletal disorders (osteoarthritis, joint pain), hypertension (HTN), cataract, depression, diabetes mellitus, and hearing problems.[6],[7],[8]

As per the WHO, HTN or elevated blood pressure is a serious medical condition that significantly increases the risks of heart, brain, kidney, and other diseases and is a major cause of premature death worldwide.[9]

Worldwide, around 1.28 billion adults aged 30–79 years have HTN, and most (two-thirds) of them living in low-and middle-income countries like India.[9] In different parts of India, such as North, East, West, and South India, the prevalence of HTN was 14.5%, 31.7%, 18.1%, and 21.1% among rural older adults.[10] Hence, the prevalence of HTN among the rural population ranges from 14.8% in Bihar to 55% in Kerala.[11],[12] Whereas, among the urban population, it ranges from 32.67% in Rajasthan to 72% in Maharashtra.[12],[13] Studies found that the common factors significantly associated with HTN were female gender, elderly aged ≥60 years, not working elderly, lower-middle socioeconomic status (SES), overweight elderly, and diabetics, respectively.[14],[15] Apart from these factors, high salt intake, high fat intake, high WHR, psychological factors, and family history of HTN were found to be associated with HTN among older adults.[16]

Worldwide, only less than half of adults (42%) with HTN are diagnosed and treated.[9] As it is most prevalent in LMIC like India and majority of its population residing in rural areas, the public health researcher, policymakers, and program implementers should prioritize the health promotion, diagnosis, and treatment of HTN as earliest possible. This study is an effort to estimate the prevalence and determine the determinants of HTN among the rural elderly population in Tigira block, Cuttack district of Odisha.


  Methodology Top


Study design and setting

This cross-sectional study was carried out in the rural block of Tigiria in Cuttack district, Odisha, India, between June 2019 and February 2020. The study participants were residents of Tigiria block, Cuttack aged more than equal to 60 years, who were conversant, comprehensible and provided their written informed consent to participate. We excluded seriously ill, bedridden patients as well as those with severe cognitive impairment.

Sample size and sampling

Assuming the prevalence of multimorbidity among the elderly as 20%, which is our primary research question of the AHSETS Study (Assessment of Health Status of the Elderly in Tigiria block: A Syndemic approach), with 95% confidence level and width of confidence interval (CI) at 8%, the beta of 0.20 and alpha of 0.05, the minimum sample size was calculated to be 407 participants.[17] Assuming a design effect of 1.6 due to clustering and a nonresponse rate of 10%, the sample size required was rounded off to 725. Participants were selected using a cluster sampling technique from a list of 30 clusters (revenue villages) selected based on a probability proportional to size (PPS) method. Systematic random sampling method was used in each of the clusters for the identification of study households, and all eligible participants from the selected household were recruited for the study. This was done until the necessary cluster size of 25 was attained. Immediate neighboring household was approached if the selected household failed to meet the eligibility criteria.

Data collection

Data were collected by trained field investigators using a pretested tool based on Open Data Kit software installed on android tablets. Previous medical history of HTN diagnosed by a medical professional was taken as positive for HTN. Sociodemographic data were collected following the standard census of India operational definitions. SES of the participants was classified using the BG Prasad SES scale. Information on their personal habits, such as smoking, chewing tobacco, and alcohol consumption behavior, was collected. Body mass index (BMI) was calculated from participants height and weight, and classify BMI as underweight (BMI <18.5), normal (BMI 18.5–25.0) and overweight (BMI >25.0).

Quality control

Data collection was commenced after a comprehensive training of the study staff using a standardized manual of operating procedures for the study. Data were collected using tablets to reduce entry errors. Periodic verification of the data was done by the investigators by checking for its completeness, duplications, and range errors. Monitoring visits were carried out by the investigators weekly to review the data collection and protocol adherence. Existing validated tools for the Indian population were used after their translation (and back translation) into the regional language, Odia, to ensure generalizability.

Statistical analysis plan

Data extraction, transformation, and cleaning were done using MS Excel. The data were scanned for outliers and no missing value was found. Frequencies and proportions were used as descriptive measures for categorical variables and mean with standard deviation (standard deviation) for continuous variables. Bi-variate analysis was done using the Chi-square test. The binary logistic regression model was used to find out the predictors of HTN. All the statistical analysis was run in“R” software version 4.0.3.

Ethical considerations

Ethical approval was obtained from the institutional human ethics committee of ICMR-RMRC Bhubaneswar (Approval No – ICMR-RMRCB/IHEC-2019/022). Written informed consent was obtained from all participants, and the national ethical guidelines for biomedical research were followed.[18]


  Results Top


This cross-sectional study was carried out among 725 rural elderly (>60 years) people of the Cuttack district of Odisha, of which 378 (52.1%) were male. The mean age of the study participants was 70.24 years (SD = 8.37 years). Among the total elderly, 252 (34.75%) participants were diagnosed with HTN. Sociodemographic features of the study participants along with the prevalence of HTN were tabulated [Table 1]. 63.9% (n = 463) of the rural elderly were from the 60 to 69 years age group, while only 10.7% (n = 78) had completed secondary education. In comparison to men, women had a higher prevalence of HTN with increasing age. Elderly who completed secondary education and higher were more prevalence of HTN and similarly, the prevalence was high among the higher SES group. Among the ethnic group, HTN was more prevalent in general (43.7%, n = 45), followed by OBC (35%, n = 184) and SC (25.3%, n = 20) category. Common factors found to be statistically associated with HTN were gender, occupation, ethnicity, and SES. Details are given in [Table 1].
Table 1: Sociodemographic characteristics of the study population

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The logistic regression model was run to determine the predictors of the HTN among the rural elderly population. Common factors found to be significant with HTN were female gender (adjusted odds ratio [AOR] = 1.73, CI = 1.129–2.666), elderly aged ≥80 years (AOR = 1.98, CI = 1.170–3.379), not working elderly (AOR = 2.14, CI = 1.178–3.890), lower-middle SES (AOR = 1.61, 1.093–2.372), overweight elderly (AOR = 2.01, CI = 1.309–3.098) and diabetics (AOR = 4.56, CI = 2.704–7.718) respectively. Details of the predictors are tabulated in [Table 2].
Table 2: Logistic regression model for hypertension

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  Discussions Top


This cross-sectional study found a HTN prevalence of 34.75% (n = 252) among rural older adults. Similar prevalence was found in Agra (31.46%) and Gujarat (42.7%).[15],[19] In different parts of the country, such as North, East, West, and South India, the prevalence was 14.5%, 31.7%, 18.1%, and 21.1% among rural older adults.[10] Hence, the prevalence of HTN among the rural population ranges from 14.8% in Bihar to 55% in Kerala.[11],[12] Whereas, among the urban population, it ranges from 32.67% in Rajasthan to 72% in Maharashtra.[12],[13] In some countries such as Nigeria, Ethiopia, Bangladesh, and Tanzania, the prevalence of HTN among the rural older adults was found to be 26.8%, 41.9%, 53%, and 69.9%, respectively.[12],[20],[21],[22] This variation prevalence rate among the rural and urban population of different States of India might be due to the different cultural practices, food habits, and lifestyle factors such as sedentary occupation, work stress, etc., Furthermore, due to the lack of health facility, health professionals, diagnostics, and finance in rural communities, the prevalence rate was found to be less. In support of this, a very less prevalence (14.8%) of HTN was found in a Tribal population where healthcare access and the diagnostic facility is poor along with their SES but, a high prevalence (55%) was found in the rural population of Kerala where the health system is best in comparison to other States.[11],[12]

Common factors found to be significant with HTN were female gender (AOR = 1.73), elderly aged ≥80 years (AOR = 1.98), not working elderly (AOR = 2.14), lower-middle SES (AOR = 1.61), overweight elderly (AOR = 2.01), and diabetics (AOR = 4.56), respectively. These findings are also supported by the studies conducted in Central India and Gujarat by Kokiwar et al. and Sheth and Jadav.[14],[15] Apart from these factors, high salt intake, high fat intake, high WHR, psychological factors, and family history of HTN were found to be associated with HTN among older adults.[16] The similar risk factors for HTN were found in various studies of other countries such as Bangladesh, Nepal, China, Nigeria, and Ethiopia.[12],[20],[21],[23],[24] Some studies have found an inverse association of unmarried status, physical activity, rural residence, and use of alcohol and tobacco with HTN; this means these factors are protecting toward the development of HTN.[12],[25],[26] The rural residency as protecting factor may be due to the less prevalence of HTN among them in comparison to the urban residency, but the use of alcohol and tobacco could not be a protecting factor which is a risk factor for most of the noncommunicable diseases along with HTN.

The health promotion models to prevent and reduce noncommunicable diseases should be implicated and monitored accordingly at the primary health-care levels. The diagnostic curative facility for the same should be available for timely management of the diseases and to prevent complications. The Free Drugs and Diagnostic Service Initiative Scheme already started by the National Health Mission in India which providing free diagnostic and drugs facility starting from the Sub center level, but proper monitoring is the key issue here.[27] Furthermore, Centrally sponsored health programs such as “National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke (NPCDCS)” and “National Programme for Health Care of the Elderly (NPHCE)” are in place, but still the prevalence of noncommunicable disease like HTN is high. The policymakers and implementers should evaluate the schemes and manage them as required.


  Conclusion Top


HTN prevalence was found to be high in rural area, and most of the sociodemographic factors were significantly associated with the risk of HTN. The factors such as female gender, elderly aged ≥80 years, not working elderly, lower-middle SES, overweight elderly and diabetes were found to be the determinants of HTN in the rural elderly population of Odisha.

Strength and limitation

This study collected the health information of the elderly at the grass root level, which will be helpful to researchers and policymakers. The limitation of this study is that the disease status which was previously diagnosed was collected. The prevalence may vary with real-time diagnosis of HTN.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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    Tables

  [Table 1], [Table 2]



 

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