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Research Article | Volume 15 Issue 9 (September, 2025) | Pages 137 - 142
Socio-demographic Factors and Hypertension Control: A Case-Control Study in Coastal Kerala, India
 ,
 ,
1
Assistant Professor, Department of Community Medicine, Govt. T.D. Medical College Alappuzha
2
Professor, Department of Community Medicine, Sree Gokulam Medical College and Research Foundation Thiruvananthapuram
3
Professor, Department of General Medicine, Sree Gokulam Medical College and Research Foundation, Thiruvananthapuram
Under a Creative Commons license
Open Access
Received
July 16, 2025
Revised
Aug. 15, 2025
Accepted
Aug. 27, 2025
Published
Sept. 6, 2025
Abstract

Hypertension is a major public health challenge globally, particularly in India where control rates remain low. This case-control study aimed to identify socio-demographic factors determining hypertension control among patients registered in the NCD clinic at UHTC Ambalapuzha, Kerala. The study included 182 cases (hypertensive patients with controlled blood pressure) and 182 controls (hypertensive patients with uncontrolled blood pressure). Data on socio-demographic factors including age, gender, education, occupation, ration card type, and participation in self-help groups were collected. The mean age of cases was 64.27 ± 9.3 years and controls was 65.13 ± 9.16 years. The majority of participants were females (65.4% in cases, 58.8% in controls). Most participants had low education levels, with 38.5% of cases and 39% of controls having studied up to 8th-10th standard. Over half of the participants in both groups were unemployed, and more than three-fourths had BPL ration cards. No significant associations were found between hypertension control and age, gender, education, occupation, or ration card type. However, participation in self-help groups (Kudumbashree/Ayalkkoottam) was significantly associated with hypertension control (OR: 1.942, 95% CI: 1.145-3.292, p=0.013). The study concludes that while traditional socio-demographic factors may not significantly influence hypertension control in this population, community-based self-help groups appear to play a beneficial role and could be leveraged in hypertension control programs.

Keywords
INTRODUCTION

Hypertension, defined as systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or current use of antihypertensive medication, is a major public health challenge globally [1]. It is a leading risk factor for cardiovascular diseases, stroke, renal failure, and premature mortality [2]. The global prevalence of hypertension among adults aged 30-79 years was estimated at 33% in 2019, affecting approximately 1.3 billion people worldwide [3]. In India, the prevalence of hypertension ranges from 22.6% to 31% among adults, with particularly high rates reported in Kerala (30.4% to 72%) [4-6].

Despite the availability of effective antihypertensive medications, hypertension control rates remain suboptimal globally and in India. Worldwide, only 21% of hypertensive patients have their blood pressure under control [3]. In India, awareness, treatment, and control rates are even lower, with only 37% of hypertensive individuals aware of their condition, 30% receiving treatment, and 12-15% achieving adequate blood pressure control [4,7]. Uncontrolled hypertension significantly increases the risk of cardiovascular events, with studies showing that it doubles the risk of cardiovascular disease among adults with hypertension [8].

Socio-demographic factors have been extensively studied as potential determinants of hypertension control. Previous research has yielded inconsistent results regarding the influence of age, gender, education, occupation, and socioeconomic status on hypertension control [9-11]. Some studies have reported better control among older adults [12], while others have found an inverse relationship with age [13]. Similarly, gender differences in hypertension control have been reported, with some studies showing better control among women [14] and others among men [15].

The role of community-based self-help groups in chronic disease management has gained attention in recent years. In Kerala, Kudumbashree, a women-oriented community-based self-help group network, has been actively involved in various health promotion activities at the grassroots level [16]. These groups may potentially influence hypertension control through health education, peer support, and improved access to healthcare services [17].

Despite the high burden of hypertension in Kerala and the presence of active self-help groups like Kudumbashree, limited research has examined the socio-demographic determinants of hypertension control in this context. Understanding these factors is crucial for developing targeted interventions to improve hypertension control rates. Therefore, this study aimed to identify the socio-demographic factors associated with hypertension control among patients registered in the NCD clinic at UHTC Ambalapuzha, Kerala, with a particular focus on the role of self-help group participation

MATERIAL AND METHODS

Study Design and Setting

A case-control study was conducted at the Non-Communicable Disease (NCD) clinic of the Urban Health Training Centre (UHTC) in Ambalapuzha, Kerala. The UHTC caters to the population of Ambalapuzha South Gramapanchayath, a coastal area in Alappuzha district. The NCD clinic operates five days a week (Monday to Friday) and provides care for patients with various non-communicable diseases, including hypertension.

 

Sample Size

The sample size was calculated to detect an odds ratio of 1.8 with 80% power and a 5% level of significance, assuming a 25% exposure rate among controls. The required sample size was 182 cases and 182 controls.

 

Study Population and Sampling

All hypertensive patients registered under the NCD clinic at UHTC Ambalapuzha were eligible for inclusion in the study. Using a consecutive sampling method, patients attending the NCD clinic for their regular monthly follow-up were recruited into the study until the required sample size was achieved. Patients were categorized into cases (controlled hypertension) and controls (uncontrolled hypertension) based on their blood pressure recordings.

 

Operational Definitions

  • Case: A hypertensive patient registered and being treated in the NCD clinic at UHTC Ambalapuzha, whose previous two BP recordings show adequate control (SBP < 140 mm Hg and DBP < 90 mm Hg) and the BP recording on the day of data collection also shows adequate control.
  • Control: A hypertensive patient registered and being treated in the NCD clinic at UHTC Ambalapuzha, whose at least one of the two previous Blood Pressure recordings shows no adequate control (SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg) and/or the Blood Pressure recording on the day of data collection shows no adequate control.

 

Inclusion Criteria

  • Hypertensive patients registered at the NCD clinic, UHTC Ambalapuzha
  • Age ≥ 18 years
  • Willing to provide informed consent

 

Exclusion Criteria

  • Patients with secondary hypertension
  • Pregnant women
  • Patients with severe comorbidities (e.g., advanced cancer, end-stage renal disease)
  • Non-compliance with follow-up (less than two follow-up visits in the past year)
  • Inability to provide informed consent

 

 

Data Collection

Data were collected by the principal investigator using a semi-structured interview schedule prepared in Malayalam. The purpose of the study was explained to potential participants, and written informed consent was obtained before data collection. The following information was collected:

  1. Socio-demographic factors:
    • Age (in years)
    • Gender (male/female)
    • Education (number of years of formal education, with 0 indicating no formal education)
    • Occupation (categorized as nil/unemployed, farmer, fisheries, government jobs, manual labourer, NREG, prawn peeling, self-employed, skilled, unskilled)
    • Ration card type (BPL/APL as a proxy for socioeconomic status)
  2. Participation in self-help groups:
    • Active participation in Kudumbashree/Ayalkkoottam (yes/no)

Blood pressure measurements were obtained from the patients' NCD cards, which contained records of previous two BP readings. On the day of data collection, BP was measured using a standardized protocol with Automatic BP monitors (Omron HEM-7120) after the participant had rested for at least 5 minutes. Two readings were taken 5 minutes apart, and the average was recorded.

 

Statistical Analysis

Data were analyzed using SPSS version 27. Descriptive statistics were used to summarize the characteristics of the study population. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were expressed as frequencies and percentages. The chi-square test was used to assess associations between categorical variables and hypertension control status. Odds ratios (OR) with 95% confidence intervals (CI) were calculated to measure the strength of associations. A p-value of less than 0.05 was considered statistically significant.

Ethical Considerations

The study protocol was approved by the Institutional Research Committee and the Institutional Ethics Committee of Government TD Medical College, Alappuzha. All participants provided written informed consent before inclusion in the study. Privacy and confidentiality of participants were maintained throughout the study.

RESULTS

The study included 182 cases (hypertensive patients with controlled blood pressure) and 182 controls (hypertensive patients with uncontrolled blood pressure). The socio-demographic characteristics of the study participants are presented in Table 1.

 

Table 1: Socio-demographic characteristics of study participants

Variable

Cases (n=182)

Controls (n=182)

p-value

Age (years), mean ± SD

64.27 ± 9.3

65.13 ± 9.16

0.312

Gender, n (%)

 

 

 

Female

119 (65.4)

107 (58.8)

0.186

Male

63 (34.6)

75 (41.2)

 

Occupation, n (%)

 

 

 

Nil/Unemployed

103 (56.6)

98 (53.8)

0.578

Farmer

1 (0.5)

2 (1.1)

 

Fishermen

13 (7.1)

14 (7.7)

 

Govt. jobs

2 (1.1)

3 (1.6)

 

Manual labourer

15 (8.2)

24 (13.2)

 

NREG work

17 (9.3)

10 (5.5)

 

Prawn peeling

15 (8.2)

11 (6.0)

 

Self employed

6 (3.3)

8 (4.4)

 

Skilled

5 (2.7)

9 (4.9)

 

Unskilled

2 (1.1)

3 (1.6)

 

Ration card type, n (%)

 

 

 

BPL

145 (79.7)

138 (75.8)

0.327

APL

37 (20.3)

44 (24.2)

 

 

The mean age of cases was 64.27 ± 9.3 years (range: 38-87 years), while the mean age of controls was 65.13 ± 9.16 years (range: 30-86 years). There was no significant difference in mean age between cases and controls (p=0.312). The majority of participants in both groups were female, with 65.4% of cases and 58.8% of controls being female, though this difference was not statistically significant (p=0.186).

 

More than half of the participants in both groups were unemployed (56.6% of cases and 53.8% of controls). The most common occupations among employed participants were manual laborer, NREG (National Rural Employment Guarantee) work, and fishermen. There were no significant differences in occupation distribution between cases and controls (p=0.578).

The majority of participants in both groups had BPL (Below Poverty Line) ration cards (79.7% of cases and 75.8% of controls), indicating low socioeconomic status. The difference in ration card type distribution between cases and controls was not statistically significant (p=0.327).

 

Table 2 presents the education level distribution of the study participants.

Table 2: Education level distribution of study participants

Education level (years of schooling)

Cases (n=182)

Controls (n=182)

p-value

0 (No formal education)

16 (8.8)

11 (6.0)

0.721

1

3 (1.6)

0 (0.0)

 

2

3 (1.6)

7 (3.8)

 

3

11 (6.0)

8 (4.4)

 

4

23 (12.6)

20 (11.0)

 

5

14 (7.7)

24 (13.2)

 

6

4 (2.2)

14 (7.7)

 

7

21 (11.5)

10 (5.5)

 

8

12 (6.6)

16 (8.8)

 

9

11 (6.0)

8 (4.4)

 

10

47 (25.8)

47 (25.8)

 

11

0 (0.0)

3 (1.6)

 

12

13 (7.1)

5 (2.7)

 

Graduate

4 (2.2)

7 (3.8)

 

Postgraduate

0 (0.0)

2 (1.1)

 

 

The education levels were generally low in both groups, with 8.8% of cases and 6.0% of controls having no formal schooling. The highest proportion of participants in both groups (25.8%) had studied up to 10th standard. Only a small proportion of participants had attained higher education, with 2.2% of cases and 4.9% of controls having a graduate or postgraduate degree. There were no significant differences in education level distribution between cases and controls (p=0.721).

 

 

 

 

 

Table 3 presents the association between self-help group participation and hypertension control.

 

Table 3: Association between self-help group participation and hypertension control

Self-help group participation

Cases (n=182)

Controls (n=182)

Crude OR (95% CI)

p-value

Yes

46 (25.3)

27 (14.8)

1.942 (1.145-3.292)

0.013

No

136 (74.7)

155 (85.2)

Reference

 

 

Active participation in self-help groups (Kudumbashree/Ayalkkoottam) was significantly associated with hypertension control. Among cases, 25.3% reported participating in self-help group activities, compared to 14.8% of controls. The odds of having controlled hypertension were 1.942 times higher among those who participated in self-help groups compared to those who did not (95% CI: 1.145-3.292, p=0.013).

DISCUSSION

This case-control study examined socio-demographic factors associated with hypertension control among patients registered at the NCD clinic in UHTC Ambalapuzha, Kerala. The findings indicate that while traditional socio-demographic factors such as age, gender, education, occupation, and socioeconomic status were not significantly associated with hypertension control in this population, participation in community-based self-help groups showed a significant positive association.

The mean age of the study participants was approximately 64-65 years, reflecting the typical age distribution of hypertensive patients seeking care at NCD clinics [18]. The lack of significant association between age and hypertension control in this study is consistent with some previous research [19,20] but contrasts with other studies that have reported better control among older adults [21] or an inverse relationship with age [22]. This inconsistency in findings across studies may be due to differences in population characteristics, healthcare systems, and access to treatment.

In this study, females constituted a higher proportion of both cases (65.4%) and controls (58.8%), though the difference was not statistically significant. The lack of significant association between gender and hypertension control aligns with findings from some studies in India [23,24] but differs from others that have reported better control among women [25] or men [26]. These mixed results suggest that gender differences in hypertension control may be context-specific, influenced by cultural, social, and healthcare system factors.

Education level was not significantly associated with hypertension control in this study, despite the generally low educational attainment among participants. This finding is consistent with some previous research [27,28] but contrasts with studies that have reported better hypertension control among individuals with higher education [29,30]. The lack of association in this study may be partly explained by the relatively uniform low educational status across the study population, which could have limited the ability to detect differences. Additionally, all participants received behavior change communication from treating physicians, which may have mitigated the potential influence of education on hypertension control.

Occupation and socioeconomic status (as indicated by ration card type) were also not significantly associated with hypertension control in this study. The high proportion of unemployed participants (over 50% in both groups) and the predominance of BPL ration card holders (over 75% in both groups) reflect the disadvantaged socioeconomic status of the study population. Similar to education, the lack of variability in these factors may have limited the ability to detect associations. Previous studies have reported mixed results regarding the influence of occupation and socioeconomic status on hypertension control, with some finding better control among those with higher socioeconomic status [31] and others reporting no significant association [32].

The most significant finding of this study was the positive association between participation in self-help groups (Kudumbashree/Ayalkkoottam) and hypertension control. Participants who actively engaged in self-help group activities had nearly twice the odds of having controlled hypertension compared to those who did not participate. This finding highlights the potential role of community-based interventions in chronic disease management.

Self-help groups like Kudumbashree may influence hypertension control through several mechanisms. These groups provide a platform for health education, raising awareness about hypertension and its management [17]. They also offer social support, which can enhance medication adherence and lifestyle modifications [16]. Additionally, self-help groups may facilitate access to healthcare services and empower individuals to take a more active role in managing their health [16]. In Kerala, where the health sector is decentralized, self-help groups like Kudumbashree play a crucial role in bridging the gap between communities and the healthcare system [17].

The finding that self-help group participation is associated with better hypertension control has important implications for public health practice. It suggests that integrating community-based self-help groups into hypertension control programs could be an effective strategy to improve control rates. This is particularly relevant in resource-limited settings like India, where healthcare infrastructure may be constrained. Leveraging existing community networks like Kudumbashree could provide a cost-effective approach to enhancing hypertension control at the population level.

Several limitations of this study should be acknowledged. First, the case-control design does not allow for causal inferences, and the observed associations may be influenced by unmeasured confounding factors. Second, the study was conducted in a single NCD clinic in a coastal area of Kerala, which may limit the generalizability of the findings to other settings. Third, the study relied on self-reported information for some variables, which may be subject to recall and reporting bias. Finally, the study did not examine other potentially important factor such as medication adherence which could influence hypertension control.

Despite these limitations, this study provides valuable insights into the socio-demographic factors associated with hypertension control in a rural coastal population in Kerala. The findings suggest that while traditional socio-demographic factors may not significantly influence hypertension control in this population, community-based self-help groups appear to play a beneficial role. This highlights the importance of considering social and community contexts in the design and implementation of hypertension control programs.

CONCLUSION

This case-control study examined socio-demographic factors associated with hypertension control among patients registered at the NCD clinic in UHTC Ambalapuzha, Kerala. The findings indicate that traditional socio-demographic factors such as age, gender, education, occupation, and socioeconomic status were not significantly associated with hypertension control in this population. However, participation in community-based self-help groups (Kudumbashree/Ayalkkoottam) showed a significant positive association with hypertension control, with participants who engaged in self-help group activities having nearly twice the odds of having controlled hypertension.

The study highlights the potential role of community-based interventions in chronic disease management and suggests that integrating self-help groups into hypertension control programs could be an effective strategy to improve control rates, particularly in resource-limited settings. The findings have important implications for public health practice and policy, emphasizing the need to consider social and community contexts in the design and implementation of hypertension control programs

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