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 Table of Contents  
Year : 2021  |  Volume : 6  |  Issue : 3  |  Page : 142-148

Evaluation of association of psychosocial stress and hypertension in adults >30 years of age: A community-based case–control study from Rural Central India

Department of Community Medicine, Mahatma Gandhi Institute of Medical Science, Sewagram, Wardha, Maharashtra, India

Date of Submission23-Jul-2021
Date of Decision06-Sep-2021
Date of Acceptance17-Sep-2021
Date of Web Publication22-Nov-2021

Correspondence Address:
Dr. Sneha Yadav
Mahatma Gandhi Institute of Medical Science, Sewagram, Wardha - 442 102, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jncd.jncd_41_21

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Background: Hypertension has multifactorial causation. Stress has chronically been cited as an imperative cause of hypertension among other risk factors such as sleep abnormalities. The interrelation between psychosocial stress and hypertension has been significant though the exact association remains debatable.
Objective: The objective of the study was to evaluate the association of psychosocial stress and other factors such as family and social support, sleep abnormalities, physical activity, and addiction with hypertension in adults >30 years of age.
Materials and Methods: Age- and sex-matched community-based case–control study with 90 incident hypertensive cases aged (>30) and 90 controls were selected from rural populations in central India. Study participants were examined and interviewed regarding their sociodemographic characteristics, psychosocial stress, family and social support, quality of sleep, addiction, and physical activity using four structured and validated questionnaires. Data analysis was done by binomial logistic regression with SPSS (version 21).
Results: Psychosocial stress was significantly associated with incident hypertension (adjusted odds ratio [AOR] =8.198, 95% confidence interval [C.I.] 2.85–23.52). Participants having compromised family and social support (AOR = 3.0, 95% C.I: 1.41–6.34), poor quality of sleep (AOR = 4.429, 95% C.I: 1.78–10.96), and low physical activity (AOR = 2.92, 95% C.I: 1.22–6.98) had higher odds of developing hypertension. Sedentary occupation, lower socioeconomic status, and body mass index ≥23 kg/m2 each had an association with hypertension.
Conclusion: This study highlights a significant number of undiagnosed or untreated cases of psychosocial distress in the community. Thus, calling for immediate attention toward psychosocial stress as an important etiological determinant of hypertension.

Keywords: Family support, hypertension, psychosocial stress, sleep quality

How to cite this article:
Yadav S, Garg S, Raut AV. Evaluation of association of psychosocial stress and hypertension in adults >30 years of age: A community-based case–control study from Rural Central India. Int J Non-Commun Dis 2021;6:142-8

How to cite this URL:
Yadav S, Garg S, Raut AV. Evaluation of association of psychosocial stress and hypertension in adults >30 years of age: A community-based case–control study from Rural Central India. Int J Non-Commun Dis [serial online] 2021 [cited 2023 Mar 26];6:142-8. Available from: https://www.ijncd.org/text.asp?2021/6/3/142/330911

  Introduction Top

People living and working in rural and remote communities face a variety of stressors including unpredictable climate change, fluctuating market conditions, financial strain, social deprivation, and limited access to basic public and health services. Hypertension is a disease entity that largely remains silent during its clinical course and not only poses an important public health problem but it is also an independent risk factor for other cardiovascular diseases, which are an important cause of mortality.[1] Studies have shown a steady rise in the prevalence of hypertension in the previous decade. The overall prevalence of hypertension in India is 29.8%. Significant prevalence of hypertension 33.8% has also been noted in rural parts of India including that of rural central India.[2],[3] In a rural community where obesity is not common, physical activity is intense due to the occupation, and harmful use of alcohol and smoking is limited; there was a need to identify other risk factors for developing hypertension. In this regard, stress and sleep abnormalities have long been identified as potential risk factors for hypertension.[4] Stress includes components that affect the individual physiologically, psychologically, socially, and emotionally. Overall, there has been less evidence for psychological factors as a predictor of hypertension, with most of the evidence indicating anger, anxiety, and depression. Increasing prevalence of hypertension in the world including India is a cause to search for more etiological factors affecting it which has not been explored in the past. Studies have already examined factors such as age, genetic factors, socioeconomic status, gender, alcohol, and smoking as definitive causes for rise in blood pressure. Understudied causes such as psychosocial stress and quality of sleep are also contributors and can pose a significant risk as shown by previous studies,[5] thus emphasizing the need for further studies in these areas. The aim of this study was to evaluate the association of psychosocial stress and other factors such as family and social support and sleep abnormalities with hypertension.

  Materials and Methods Top

The study was a community-based age- and sex-matched case–control study. One hundred and eighty adults of more than 30 years of age participated in the study (90 cases and 90 controls). Written informed consent was obtained from all study participants before their inclusion in the study. Furthermore, approval was obtained from the Institutional Ethics Committee before the start of the study through letter approval no. MGIMS/IEC/COMMED/39/2019. Both cases and controls were selected from the same study base. Cases were defined as any previously undiagnosed subject, either male or female, of age more than 30 years who is diagnosed as a new case (prehypertensive and hypertensive) according to JNC-8 criteria at the time of the study. A door-to-door survey was conducted, and adults >30 years of age were screened to identify the incident cases of hypertension. From the identified incident cases, 90 participants, who provide written informed consent for participation, were included in the study through consecutive sampling. Controls were defined as any previously undiagnosed subject, either male or female, of age more than 30 years who is normotensive according to JNC-8 criteria at the time of study. Age (within an interval of 2 years) and sex-matched controls were selected from those who were found to be normotensive at the time of screening through consecutive sampling. Inclusion criteria for both cases and controls included only those >30 years of age who are willing to respond to the study questionnaire and study procedures. All those who were suffering from any chronic illness (diabetes, cardiovascular diseases, stroke, cancer, depression, asthma, allergies, chronic skin diseases, and tuberculosis among others) were excluded from the study. Prevalent cases (previously diagnosed hypertension) and pregnant females were also excluded from the study. The interviewers were blinded to the case/control status of the participants.

Sample size

Sample size was estimated to be 180 participants (90 cases and 90 controls) using Epi Info™ 7.1.5 software with the following assumptions:

  • α =0.05
  • CI = 95%
  • Power = 90%
  • P (proportion of controls who were exposed) =38.45%[6]
  • Ratio of cases to controls = 1:1
  • Hypothesized odds ratio = 3[7]
  • Nonresponse rate = 10%

Study tools

  • Indian Council of Medical Research (ICMR) psychosocial stress scale (Srivastava 1991-92)[8]
  • The Alcohol, Tobacco Involvement Screening Test (ASSIST) developed by the World Health Organization (WHO) to assist with the identification of tobacco and alcohol use.[9]
  • WHO Global Physical Activity Questionnaire (GPAQ) for physical activity surveillance.[10]
  • Pittsburgh Sleep quality index (PSQI) to assess the quality of sleep.[11]


Blood pressure measurement

A standard and calibrated nonmercury sphygmomanometer (Diamond Deluxe Blood Pressure apparatus, Pune, India) had been used throughout the study to minimize the instrumental error. Training in all relevant techniques was obtained by the observer including care for avoiding expectation error and digit preference. All the blood pressure readings were recorded by a single observer along with auscultatory determination to reduce the interobserver variation. The forearm and sphygmomanometer were kept at the level of the heart. Casual blood pressure reading was taken by the observer for every individual as per the guidelines of WHO and JNC-8. The participants were made to sit on the chair comfortably. It was ensured that the participants had not made any vigorous effort during preceding 60 min, smoked or taken coffee or tea, food, and had sound sleep on the previous night. All readings were taken on the right arm. Three readings of blood pressure were taken. Each reading was taken about 3 min apart, and average reading of the last two readings was noted. If the first reading differed by more than 5 mm of Hg, additional reading was taken, and an average of the three readings was noted.

Measurement of body mass index

Height (cm) was measured with a wall stadiometer (SECA 222, Germany), and weight (Kg) was obtained with a digital scale (OMRON body composition monitor scale HBF-212, Japan). Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. BMI values were used to define weight categories according to the WHO Asia-Pacific criteria for BMI.[12] Weight and height were measured using standard calibrated electronic weighing scales and stadiometer as described in the WHO STEPS surveillance module.[13] Cases and controls having BMI more than or equal to 23 were placed in the “pre-obese/obese category” and those <23 were placed in the “thin/normal (non-obese) category.”

Psychosocial stress

ICMR psychosocial stress scale (60 items) measure participant's perception of feeling stressed. The stress questionnaire queried participants on operational social stressors over the last 1 year in following spheres of social interaction: person-self, family, relatives, neighborhood, peer group, workplace, community, or society. In addition to the questionnaire, a short measure of stress arising from infrequent but crucial life events that occurred in respondent's personal/social life in the past 1 year was also assessed. Responses were on a 4-point scale from “Not at all” to “often.” Scores were summed to indicate current stress levels, with lesser scores suggesting higher perceived stress. Before analysis, the sum score (range 0–180) was divided into quartiles with 75th percentile being the cutoff for “high stress” (≤139) and “low stress” (>139).[8]

Family and social support

Family and social support was measured using ICMR questionnaire (33 item) which assessed factors such as support of family, support of relatives, support of neighbors, relationship with friends, relationship with colleagues, community efforts for sanitation, medical facilities, social discrimination, social contacts, community information, law and order problems, caste, and religion. Responses were on a 3-point scale: Not really; to some extent; Very much. Median score of 78 was taken as cut off for “Good” (≥78) and “Compromised” (<78) Family and Social Support.[8]

Physical activity

Self-reported physical activity was obtained using WHO GPAQ, which obtains information about participant's habitual activities in three domains: work, transportation, and leisure. Cases and controls on the basis of scores obtained by the GPAQ were grouped into heavy and moderate as having “heavy” physical activity and low as “low” physical activity.[10]

Quality of Sleep

Quality of sleep was evaluated through the PSQI. PSQI assessed participant's sleep quality of the past 12 weeks and was administered during the personal interview. A global PSQI ≥5 has a diagnostic sensitivity of 89.6% and specificity of 86.5% in distinguishing “poor sleepers” (PSQI ≥5) from “good sleepers” (PSQI <5) participants.[14]


We used the WHO ASSIST as a screening tool for “ever users” or “never users” of any form of addiction (Tobacco and Alcohol). We did not intend to use the grades of addiction in our study. Hence all those who used any form of addiction were categorized in “ever users” and those who did not have any form of addiction were categorized as “never users.”[9]


All participants having occupation as farmers, daily wage laborers and housewives were placed under the “heavy/moderate” occupation group and those having sedentary occupation such as shopkeepers, office workers, and not doing any job were classified in the “sedentary occupation” group.

Marital status

All participants those who were married or had a partner were categorized as “living with a partner.” Those who were divorced, widowed, separated, or single were categorized as “living without partner.”

Socioeconomic status

Ration card was used as a proxy measure for assessing the socioeconomic status of participants. Participants with yellow or antyodayi ration card were classified as below poverty line (BPL), while others with the orange and white card were classified as non-BPL.

Data entry and analysis

Data were collected in a paper-less manner using Open Data Kit Kobo Humanitarian toolbox (Harvard Humanitarian Initiative and OCHA), and analysis was done using SPSS (version 21) software.

The collected data were entered in the excel sheet and analyzed using:

  • Descriptive analysis using frequency and percentage
  • Bivariate analysis using matched odds ratio with 95% confidence level
  • Multivariate analysis using binomial logistic regression. Logistic regression analysis was used to determine the association of variable with hypertension, and P < 0.05 was taken as statistically significant.

Confidentiality and quality control

The identity of study participants was kept confidential by assigning them a unique identification number. The details of the study participants were not disclosed to anyone. Data quality was checked before analysis.

  Results Top

Mean age among the cases was 49.55 years (±11.86 years), while in controls, it was 49.47 years (±11.84 years). Mean systolic blood pressure in cases was 152.9 mm/Hg (±13.48 mm/Hg) and diastolic blood pressure was 93.68 mm/Hg (±7.91 mm/Hg). Mean systolic blood pressure in controls was 111.63 mm/Hg (±6.17 mm/Hg) and diastolic blood pressure was 74.7 mm/Hg (±4.43 mm/Hg). Education level was found to be equally distributed among cases and controls (case vs. control 57.80% vs. 56.70%, >10 years of schooling). Occupation and marital status were comparable in both cases and controls. Nearly 90% of our study participants were non-BPL reflecting the general socioeconomic status of study participants [Table 1].
Table 1: Demographic characteristics of study participants

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Nearly 75.5% of the study participants had high psychosocial stress. Psychosocial stress was present in 93.3% of cases and 57.8% of controls. Around 56.1% of all study participants reported having good family and social support. Poor quality of sleep in the cases was 76.7%, while it was 53.40% in controls. Overall, 65% of study participants reported the poor quality of sleep. Nearly 61.1% of study participants had moderate/heavy physical activity. Most of the study participants did not have any form of addiction (80.5%). Average BMI in cases was 23.9 ± 4.12 and in controls was 22.1 ± 3.23 [Table 2].
Table 2: Risk factor profile among cases and control

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[Table 3] shows that participant with high psychosocial stress had higher odds (mOR = 9.0, 95% confidence interval [C.I.] 3.2–25.25) for developing hypertension than person with low psychosocial stress. Participants having a compromised family and social support have 4.66 times chances of developing hypertension than those having good support (mOR = 4.66, 95% C.I. 2.26–9.58). Poor quality of sleep was found to have a significant association with hypertension. Those having poor quality of sleep had 2.53 times the likelihood of developing hypertension than those having good quality of sleep.(mOR = 2.53, 95% C.I. 1.33–4.82). Marginal association was found between low physical activity and hypertension with matched odds of 1.61 (95% C.I. 0.89–2.90). Addiction was positively associated with hypertension, with a likelihood of 1.5 times of developing hypertension for person using any form of addiction than a never user (mOR = 1.5, 95% C.I. 0.67–3.30).
Table 3: Risk factors for hypertension

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Logistic regression analysis was done to determine the predictors of hypertension [Table 4]. All variables were entered in the software using ENTER method (P < 0.05 significant) “Omnibus test” for model coefficients was significant. “Nagelkerke R2” was 0.42, indicating that 42% variation in hypertension can be explained by independent predictor variables that are psychosocial stress, family and social support, quality of sleep, and physical activity after adjusting for other variables. “Hosmer Lemeshow” goodness of fit test was nonsignificant (P = 0.869) indicating the model fits the data.
Table 4: Predictors of hypertension in study participants

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Psychosocial stress had a highly significant association with hypertension (adjusted odds ratio [AOR] =8.198, 95% CI: 2.85–23.52). Participants having compromised family and social support (AOR = 3.0, 95% C.I. 1.41–6.34), poor quality of sleep (AOR = 4.429, 95% CI: 1.78–10.96), and low physical activity (AOR = 2.92, 95% C.I. 1.22–6.98) had higher odds of developing hypertension.

  Discussion Top

Our study used ICMR psychosocial stress scale developed and validated in India for the assessment of psychosocial stress. The scale assesses how different situations affect perceived stress. Effect of factors such as family and social support, sleep, physical activity, addiction and BMI were also studied. These factors could be independently associated with psychosocial stress as well. Our study found a significant statistical association of psychosocial stress with hypertension. This can be attributable to the fact that psychosocial stress is dependent on factors that directly or indirectly cause increased stressor response in the body inadvertently, leading to hypertension. We found that both the cases and controls were exposed to psychosocial stress, but the response of each person to this stress was different. Due to which not all those exposed had hypertension. We could attribute this to the significant association of family and social support. Controls had a high family and social support compared to cases, thus strengthening the fact that even though the controls were exposed to varying degrees of stress, the family and social support system provided a protective role. Sleep has shown to be a normalizer of stressor responses in the body also known as “Nocturnal dipping.” In our study, consistent to the other studies on hypertension, we found that cases had disturbed sleep pattern and that there was a significant positive association between bad quality of sleep and hypertension. This can be owed to the fact that to deal with stress one often finds himself thinking at lengths about problems and probable mechanisms to deal or escape this stressor, leading to increased worries, apprehensions and anxiety, thus deteriorating the quality of sleep. Our study being conducted in the rural setting found that physical activity was significantly associated with hypertension, but BMI did not show an association with hypertension, a marked contrast from many studies. Addiction was a factor present in very few of our participants, probably due to the fact that people in the settings had a general awareness to the harmful effects of tobacco and alcohol.

This community-based study has helped to bridge the existing evidence gap, as identified by the meta-analysis, and provide a conclusive indication, whether psychosocial stress and hypertension are associated or not. Since the study has focused on psychological component of stress unlike most studies that use general stress, its strengths lie in being population-based study. The limitations of our studies was that, being a case–control study, incidence, prevalence, and relative risk could not be adjudged; underlying which the attributable risk of psychosocial stress could not be ascertained. Furthermore, since the study was conducted only in a geographical region of central India and was mainly focused on the rural populations, the results cannot be extrapolated to other geographical populations and urban areas as psychosocial stress is highly dependent of the environmental conditions which is subject to vary.

This study concludes a significant number of undiagnosed or untreated cases of psychosocial distress in the community. This indicates the need for interventions to prevent and manage psychosocial stress through systematic screening and awareness program that is informed by locally generated evidence, thus promoting family care and strengthening social support system, coupled with effective risk communication through health-care providers would go a long way in offering primary preventive counseling.

  Conclusion Top

A significant association of hypertension with psychosocial stress was observed in rural populations of central India. Hence, screening should be done for early diagnosis of hypertension and psychosocial stress must be considered while planning treatment. Counselling for the same should play a major role along with prevention and control measures.


We thank our study participants for cooperation and participation in the research. We thank Professor and Head, Department of Community Medicine (MGIMS, Sewagram) for allowing us to use departmental infrastructure to conduct the research. We would also like to acknowledge ICMR Studentship Program – 2019 to first author Sneha Yadav (Reference ID-2019-04540) under which this project was successfully carried out.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

World Health Organization. A Global Brief on Hypertension: Silent Killer, Global Public Health Crisis: World Health Day 2013. World Health Organization; 2013.  Back to cited text no. 1
Anchala R, Kannuri NK, Pant H, Khan H, Franco OH, Di Angelantonio E, et al. Hypertension in India: A systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens 2014;32:1170-7.  Back to cited text no. 2
Bhise MD, Patra S. Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis. PLoS One 2018;13:e0191948.  Back to cited text no. 3
Heine H, Weiss M. Life stress and hypertension. Eur Heart J 1987;8 Suppl B: 45-55.  Back to cited text no. 4
Gasperin D, Netuveli G, Dias-da-Costa JS, Pattussi MP. Effect of psychological stress on blood pressure increase: A meta-analysis of cohort studies. Cad Saude Publica 2009;25:715-26.  Back to cited text no. 5
Liu MY, Li N, Li WA, Khan H. Association between psychosocial stress and hypertension: A systematic review and meta-analysis. Neurol Res 2017;39:573-80.  Back to cited text no. 6
Hu B, Liu X, Yin S, Fan H, Feng F, Yuan J. Effects of psychological stress on hypertension in middle-aged Chinese: A cross sectional study. PLoS One 2015;10:e0129163.  Back to cited text no. 7
Srivastava A. Manual for ICMR Psychological Stress Questionnaire: The 4th Advisory Committee on Mental Health. New Delhi, India: ICMR; 1991-92.  Back to cited text no. 8
WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction 2002;97:1183-94.  Back to cited text no. 9
Armstrong T, Bull F. Development of the world health organization global physical activity questionnaire (GPAQ). J Public Health 2006;14:66-70.  Back to cited text no. 10
Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193-213.  Back to cited text no. 11
WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-63.  Back to cited text no. 12
World Health Organization. WHO STEPS Surveillance Manual: The WHO STEPwise Approach to the Chronic Disease Risk Factor Surveillance. Geneva: WHO; 2005.  Back to cited text no. 13
Grandner MA, Kripke DF, Yoon IY, Youngstedt SD. Criterion validity of the Pittsburgh Sleep Quality Index: Investigation in a non-clinical sample. Sleep Biol Rhythms 2006;4:129-39.  Back to cited text no. 14


  [Table 1], [Table 2], [Table 3], [Table 4]


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