Knowledge Regarding Lifestyle Modification for Prevention of Obesity Among Adults in a Selected Urban Areas of Kanpur: A Descriptive Cross-Sectional Study

Study design

A quantitative, non-experimental descriptive cross-sectional research design was adopted to assess knowledge regarding lifestyle modification for the prevention of obesity among adults in a selected urban area of Kanpur, Uttar Pradesh, India.

Study setting

The study was conducted in the Middle-Income Group (MIG) Block located in the Panki area of Kanpur, Uttar Pradesh. The setting was selected as it represented an accessible urban community in which adults from different sociodemographic backgrounds could be recruited for assessment of knowledge regarding obesity prevention.

Study population and participants

The target population comprised adults residing in the selected urban area of Kanpur. The accessible population included adults residing in the MIG Block, Panki, who fulfilled the eligibility criteria during the period of data collection.

A total of 60 adults participated in the study.

Sampling technique and sample size

A sample of 60 adults was selected using a non-probability purposive sampling technique. Participants residing in the selected MIG Block, Panki, who met the eligibility criteria and were available during the data-collection period were approached by the investigator. Eligible participants were informed about the study, and those who voluntarily agreed to participate and provided written informed consent were included. Recruitment continued until the required sample size of 60 participants was obtained.

Eligibility criteria

Inclusion Criteria

Adults were eligible to participate if they:

1. Were residents of the selected MIG Block, Panki, Kanpur.
2. Were available during the period of data collection.
3. Were able to understand Hindi or English.
4. Were willing to participate in the study.
5. Provided informed consent.

Exclusion Criteria

1. Adults were excluded if they:
2. Were unwilling to participate in the study.
3. Were seriously ill at the time of data collection.
4. Were unable to communicate or understand Hindi or English.
5. Had a condition that substantially impaired their ability to respond to the questionnaire.
6. Were healthcare professionals or students with specialised knowledge that could substantially influence the assessment.
7. Were pregnant women.

Study variables

The dependent variable was the knowledge regarding lifestyle modification for the prevention of obesity.

Selected demographic characteristics, including age, gender, educational status, occupation, monthly family income, type of diet, physical activity and previous knowledge regarding obesity prevention, were considered as participant characteristics for analysis of their association with knowledge level.

Data collection instrument

Data were collected using a structured questionnaire developed by the investigator following a review of relevant literature and available evidence regarding obesity, healthy dietary practices, physical activity and lifestyle modification.

The questionnaire consisted of two sections:

Section A: Demographic characteristics

This section collected information regarding age, gender, educational status, occupation, monthly family income, type of diet, physical activity and previous knowledge regarding lifestyle modification for obesity prevention.

Section B: Knowledge questionnaire

This section consisted of 30 multiple-choice questions assessing knowledge regarding lifestyle modification for the prevention of obesity. Each item had one correct response. A correct response was assigned a score of 1 and an incorrect response was assigned a score of 0. The total possible score ranged from 0 to 30, with higher scores indicating greater knowledge.

The knowledge items covered major areas related to obesity prevention, including basic concepts of obesity, health risks associated with obesity, healthy dietary practices, physical activity, sedentary behaviour, weight control and healthy lifestyle practices.

Validity and reliability

The content validity of the structured questionnaire was established through review by five experts from the fields of nursing and medicine. The experts assessed the items for relevance, clarity, simplicity and adequacy. Necessary modifications were incorporated based on their recommendations.

Reliability of the knowledge questionnaire was assessed using the split-half method and the Spearman–Brown correction. The obtained reliability coefficient was 0.82, indicating good internal consistency and reliability of the instrument.

Data collection procedure

Prior permission was obtained from the concerned institutional authorities before commencement of data collection. Eligible participants were approached individually and were informed about the purpose and procedure of the study. Written informed consent was obtained before participation.

The demographic information was collected first, followed by administration of the structured knowledge questionnaire. Participants were provided adequate time to complete the questionnaire. Completed questionnaires were checked for completeness and collected by the investigator while maintaining privacy and confidentiality.

Ethical considerations

Ethical principles were maintained throughout the study. Permission was obtained from the concerned institutional authorities before data collection. Participation was voluntary, and informed consent was obtained from all participants. Participants were informed that they could withdraw from the study at any time without any adverse consequences. Confidentiality and anonymity of participant information were maintained, and the collected information was used only for research purposes.

Statistical analysis

The collected data were coded, tabulated and analysed using descriptive and inferential statistics. Categorical variables were summarized using frequencies and percentages. The knowledge score was calculated from 30 multiple-choice questions, with each correct response assigned a score of 1 and each incorrect response assigned a score of 0, resulting in a possible total score ranging from 0 to 30.

The observed total knowledge scores in the present sample ranged from 11 to 27, with a mean score of 21.60 ± 3.78 and a median score of 22.5 (IQR: 19–24). The distribution of the total knowledge score was assessed using the Shapiro–Wilk test and was found to deviate significantly from normality (W = 0.935, P = 0.003).

For the primary analysis, the total knowledge score was classified into the predefined categories specified in the study instrument: inadequate, moderately adequate and adequate knowledge. This categorization was retained because the primary study objective was to examine the association between the predefined level of knowledge and selected categorical demographic variables. The limitations associated with categorizing a continuous score were considered when interpreting the findings.

The association between the categorized knowledge level and categorical demographic variables was assessed using Pearson’s chi-square test. Where the assumptions for the chi-square test were not adequately satisfied because of small expected cell frequencies, exact tests were used as appropriate. Statistical significance was assessed using a two-sided P-value of <0.05.

For comparisons involving the original continuous knowledge score, non-parametric tests were considered appropriate because the knowledge-score distribution was non-normal. The Mann–Whitney U test was applicable for demographic variables with two categories, while the Kruskal–Wallis test was applicable for variables with more than two categories.

Statistical analysis was performed using IBM SPSS Statistics, version 20.0.

A total of 60 adults from the selected urban area of MIG Block, Panki, Kanpur, were included in the study. The findings are presented according to the study objectives.

Participant characteristics

The demographic characteristics of the participants are presented in Table 1. Of the 60 participants, 45 (75.0%) belonged to the age group of 25–44 years, 13 (21.7%) were aged 45–59 years and 2 (3.3%) were above 60 years. The majority were male (43; 71.7%).

Regarding educational status, 27 (45.0%) participants were graduates, 21 (35.0%) had secondary education, 7 (11.7%) were postgraduates and 5 (8.3%) had primary education. None of the participants were illiterate.

With respect to occupation, 24 (40.0%) participants were self-employed, 19 (31.7%) were unemployed, 14 (23.3%) were private employees and 3 (5.0%) were government employees. Regarding monthly family income, 20 (33.3%) participants reported an income below ₹10,001, while 19 (31.7%) reported ₹10,001–20,001, 12 (20.0%) reported ₹20,001–30,000 and 9 (15.0%) reported more than ₹30,000.

Most participants (40; 66.7%) followed a vegetarian diet, 14 (23.3%) followed a mixed diet and 6 (10.0%) were non-vegetarian. Regarding physical activity, 30 (50.0%) participants reported an active level of physical activity, 24 (40.0%) reported moderate activity and 6 (10.0%) reported a sedentary lifestyle. Previous knowledge regarding lifestyle modification for obesity prevention was reported by 45 (75.0%) participants, whereas 15 (25.0%) had no previous knowledge.

Knowledge regarding lifestyle modification for obesity prevention

The distribution of participants according to their level of knowledge is presented in Table 2.

Among the 60 participants, 30 (50.0%) had adequate knowledge, 24 (40.0%) had moderately adequate knowledge and 6 (10.0%) had inadequate knowledge regarding lifestyle modification for the prevention of obesity.

Thus, 54 (90.0%) participants demonstrated either moderately adequate or adequate knowledge, whereas 6 (10.0%) demonstrated inadequate knowledge.

Distribution of total knowledge score

The total knowledge score ranged from 11 to 27 among the 60 participants. The mean knowledge score was 21.60 ± 3.78, while the median score was 22.5 (IQR: 19–24). The Shapiro–Wilk test indicated that the distribution of the total knowledge score significantly deviated from normality (W = 0.935, P = 0.003). Therefore, the predefined knowledge-level categories were retained for the primary association analysis in accordance with the stated study objective.

Association between level of knowledge and selected demographic variables

The association between the level of knowledge regarding lifestyle modification for prevention of obesity and selected demographic variables was assessed. The total knowledge score was non-normally distributed (Shapiro–Wilk W = 0.935, P = 0.003). For the primary analysis, the predefined knowledge categories of inadequate, moderately adequate and adequate knowledge were therefore used to examine associations with the categorical demographic variables.

No statistically significant association was observed between level of knowledge and age (χ² = 4.391, df = 4, exact P = 0.193), gender (χ² = 0.246, df = 2, exact P = 0.845), educational status (χ² = 7.875, df = 6, exact P = 0.241), occupation (χ² = 5.761, df = 6, exact P = 0.512), monthly family income (χ² = 7.927, df = 6, exact P = 0.205), type of diet (χ² = 1.053, df = 4, exact P = 0.860), or physical activity (χ² = 5.704, df = 4, exact P = 0.158).

However, a statistically significant association was observed between previous knowledge regarding obesity prevention and level of knowledge (χ² = 30.000, df = 2, exact P < 0.001). Participants who reported previous knowledge were more frequently represented in the adequate knowledge category, whereas none of the participants without previous knowledge were classified as having adequate knowledge. The detailed findings are presented in Table 3.

The present study assessed knowledge regarding lifestyle modification for the prevention of obesity among 60 adults residing in a selected urban area of Kanpur. The study is relevant in view of the increasing burden of obesity and other metabolic non-communicable diseases in India. The ICMR-INDIAB national study involving more than 113,000 participants reported a generalised obesity prevalence of 28.6% and abdominal obesity prevalence of 39.5%, with most metabolic non-communicable diseases being more frequent in urban than rural populations [1].

In the present study, three-fourths of the participants were aged 25–44 years and nearly three-fourths were male. The sample also had a relatively high educational profile, with 45% being graduates. Most participants reported some level of physical activity, and 75% reported previous knowledge regarding lifestyle modification for obesity prevention. These characteristics are important when interpreting the knowledge findings because previous exposure to health information may influence participants’ ability to recognize obesity risk factors and preventive measures.

The present study found that 50% of participants had adequate knowledge and 40% had moderately adequate knowledge, while 10% had inadequate knowledge. Thus, although most participants demonstrated at least moderately adequate knowledge, a measurable proportion had insufficient knowledge. This finding is broadly consistent with evidence from India demonstrating variability in knowledge concerning obesity, nutrition and physical activity. A community-based study from urban South India found that 60.3% of participants scored below 50% on knowledge assessment concerning overweight and obesity, indicating substantial knowledge gaps in some urban populations [2].

Another Indian study among apparently healthy adults found that individuals with higher educational attainment had significantly higher nutrition and physical activity knowledge. The study also highlighted the need to strengthen health education efforts so that knowledge can be translated into appropriate dietary and physical activity practices [3]. In contrast, the present study did not demonstrate a statistically significant association between educational status and knowledge level. This difference may be related to the relatively small sample size and the educational distribution of the present participants, among whom no participant was illiterate and nearly half were graduates.

The present study identified previous knowledge regarding obesity prevention as the only reported demographic characteristic significantly associated with knowledge level. Participants who reported previous exposure to information had better knowledge than those who reported no previous knowledge. This finding supports the importance of access to understandable and relevant health information. Previous research has demonstrated that health literacy is related to obesity-related outcomes, and inadequate health literacy may represent a modifiable barrier to effective obesity prevention and management [4,5].

The finding is also consistent with community-based research from India emphasizing the importance of health education. A study of urban married women in Delhi found awareness of several causes, consequences and preventive measures of obesity, but also identified misconceptions regarding obesity and recommended strengthening community health promotion and mass-media education [7]. Similarly, a mixed-methods study from Kolkata reported that participants identified lifestyle, urbanisation, behavioural factors and inadequate health education among important contributors to obesity risk and concluded that health education was fundamental to prevention [9].

Lifestyle modification remains an important component of obesity prevention. Evidence from systematic reviews indicates that interventions involving diet, physical activity and behavioural strategies can help prevent excessive weight gain. A systematic review and meta-analysis of 29 randomized trials involving 37,407 adults found that weight-gain-prevention interventions resulted in significantly less weight gain than control conditions [10]. A separate systematic review found strong evidence for an association between physical activity and prevention of weight gain in adults, with greater protection observed at higher levels of moderate-to-vigorous physical activity [11].

The results therefore have practical relevance for community health nursing. Nurses working in primary healthcare and community settings can contribute to obesity prevention through individualized counselling, nutrition education, promotion of physical activity, identification of risk factors and reinforcement of sustainable lifestyle behaviours. Indian evidence also suggests that structured health education interventions can improve obesity-related practices [12]. In an urban community intervention among women, health education was associated with improvement in dietary and physical activity parameters and weight-related outcomes [13].

In the present study, knowledge was initially measured as a numerical score ranging from 0 to 30. The observed scores ranged from 11 to 27, with a mean of 21.60 ± 3.78 and a median of 22.5. The Shapiro–Wilk test indicated a non-normal distribution of the knowledge scores. Nevertheless, the study objective specifically focused on determining the association between the predefined level of knowledge and selected demographic variables. Therefore, the predefined categories of inadequate, moderately adequate and adequate knowledge were retained for the primary association analysis. Since both the categorized knowledge outcome and the selected demographic characteristics were categorical variables, the chi-square test was used, with exact P-values considered where expected cell frequencies were small. This approach provides an analysis consistent with the stated objective while acknowledging the limitations associated with categorizing a numerical knowledge score. In addition, knowledge and actual lifestyle behaviour are distinct constructs. A participant may possess adequate knowledge but still experience barriers to healthy behaviour, including time constraints, work-related demands, environmental factors, food availability and limited motivation. Research among young adults in India has similarly identified lack of time, work commitments, easy access to unhealthy foods and lifestyle-related barriers to weight management [14].

A statistically significant association was observed between previous knowledge regarding obesity prevention and the level of knowledge (χ² = 30.000, df = 2, exact P < 0.001). Participants who reported previous knowledge were more frequently classified as having adequate knowledge, whereas participants who reported no previous knowledge were not represented in the adequate knowledge category. This finding suggests an association between prior exposure to information and the measured knowledge level in this sample. However, because the study used a cross-sectional design, the finding should not be interpreted as demonstrating a causal effect of previous exposure on knowledge.

No statistically significant association was observed between level of knowledge and age, gender, educational status, occupation, monthly family income, type of diet or physical activity in the present sample. These findings indicate that statistically significant differences in categorized knowledge level were not demonstrated for these demographic characteristics under the conditions of the present study. However, the absence of statistical significance should be interpreted cautiously because the study included only 60 participants, several demographic subgroups were small, and participants were selected using non-probability purposive sampling from a single urban locality. These factors may limit statistical power and generalizability.

Overall, the findings suggest that community adults may have a reasonable level of awareness regarding obesity prevention, but continued and targeted health education is required. Importantly, health education should not be limited to providing information; it should also focus on practical skills, goal setting, self-monitoring, culturally appropriate dietary choices and feasible physical activity strategies. Such practical approaches to physical activity and prevention are also relevant to broader lifestyle-related health promotion [15].

The present study found that 50.0% of participants had adequate knowledge regarding lifestyle modification for prevention of obesity, while 40.0% had moderately adequate knowledge and 10.0% had inadequate knowledge. The total knowledge score was non-normally distributed. For the primary objective, the predefined knowledge-level categories were therefore used to examine associations with selected categorical demographic variables. A statistically significant association was observed between previous knowledge regarding obesity prevention and level of knowledge, whereas no statistically significant association was observed with age, gender, educational status, occupation, monthly family income, type of diet or physical activity.

The findings highlight the importance of continuous community-based health education regarding healthy dietary practices, regular physical activity, reduction of sedentary behaviour, weight control and other sustainable lifestyle practices. However, the findings should be interpreted in view of the small sample size, purposive sampling and single-community setting. Knowledge should not be considered equivalent to actual lifestyle behaviour, and future studies should evaluate both knowledge and behavioural outcomes.

Limitations

1. The study included only 60 participants from a selected urban locality of Kanpur; therefore, the findings cannot be generalized to the wider adult population.
2. Non-probability purposive sampling may have introduced selection bias and limited representativeness.
3. The study assessed knowledge regarding lifestyle modification but did not objectively assess participants’ actual dietary intake, physical activity, BMI or long-term behavioural practices.
4. Data were collected using a structured self-report questionnaire and may therefore have been influenced by participants’ recall, interpretation or socially desirable responses.
5. The cross-sectional design does not permit determination of a causal relationship between previous exposure to health information and knowledge level.

Recommendations

1. Similar studies should be conducted using larger probability-based samples from multiple urban communities to improve generalizability.
2. Comparative studies may be undertaken among urban and rural adults to identify differences in knowledge and lifestyle practices.
3. Interventional studies should evaluate the effectiveness of structured nurse-led health education programmes on obesity prevention.
4. Future studies should assess knowledge together with attitude, dietary practices, physical activity, sedentary behaviour and anthropometric indicators such as BMI and waist circumference.
5. Community-based programmes should use culturally appropriate educational materials and multiple communication methods, including individual counselling, group education and audiovisual approaches.
6. Longitudinal studies should be undertaken to determine whether improved knowledge translates into sustained lifestyle modification and prevention of weight gain.
7. Future research should explore barriers that prevent adults from translating obesity-prevention knowledge into healthy lifestyle behaviours.