Obesity and modern lifestyles: Prevalence and lifestyle correlates among urban adults in Ahmedabad City

Introduction

Obesity, defined as an excessive accumulation of body fat that poses a risk to health, has become a global concern affecting both developed and developing nations. It is primarily the result of an energy imbalance between calorie consumption and expenditure, exacerbated by changes in diet, physical activity, and urban lifestyles (Janssen et al., 2004) [1] . The World Health Organization (WHO, 2021) categorizes obesity as a significant contributor to noncommunicable diseases such as cardiovascular conditions, diabetes, and certain cancers, with urban areas being particularly vulnerable. Globally, obesity prevalence has nearly tripled since 1975, with over 650 million adults classified as obese in 2016. In India, urbanization and the adoption of sedentary lifestyles have further accelerated this trend. Data from the National Family Health Survey (NFHS-5, 2019-2021) reveals that 33.2% of urban women and 29.8% of urban men are overweight or obese. Ahmedabad, a rapidly urbanizing city in Gujarat, has emerged as a focal point of this crisis. Surveys indicate that 16% of women and 12% of men in Ahmedabad are obese, surpassing national averages. The dietary patterns in urban Ahmedabad reflect a shift from traditional foods to energy-dense, nutrient-poor options, often influenced by fast food and online food delivery systems. Additionally, sedentary work environments and limited physical activity contribute to the alarming rates of obesity. Socioeconomic factors, including education, income, and occupation, further shape these trends, making obesity not just a medical condition but a social phenomenon. This study aims to explore the prevalence of obesity in Ahmedabad's adult population, focusing on its relationship with modern lifestyle factors such as dietary habits, physical activity, and socioeconomic conditions. By identifying key lifestyle correlates, the research seeks to inform interventions tailored to urban populations grappling with obesity's health and social ramifications.

Materials and Methods

Selection of location

The study's title explicitly mentions that the study was conducted in Ahmedabad city. In the Indian state of Gujarat, Ahmedabad is the most populous city. Under the Government of India's Flagship Smart Cities Mission, Ahmedabad has been chosen as one of the hundred Indian cities to be built as a smart city. Ahmedabad was considered since it is one of Gujarat's fastest expanding cities, and as a result, significant changes in the city's population's life style have happened.

Research Design

Type: Ex-post-facto design. This design is appropriate for assessing the prevalence of www.extensionjournal.com obesity and its relationship with lifestyle factors since the independent variables, such as socio-economic status, dietary habits, and physical activity, cannot be controlled or manipulated.

Respondent Selection Criteria

Population: Adults aged 20-55 years residing in Ahmedabad City.

Inclusion Criteria

• Adults willing to participate in the study.

• Citizens residing in Ahmedabad for more than one year.

Exclusion Criteria

• Pregnant and lactating women.

• Individuals with physical deformities or acute illnesses.

• Individuals undergoing active weight loss programs.

Sampling Method

Sampling Technique: Multi-stage random sampling. The city will be divided into six administrative zones (North, East, South, West, New-West, Central). A total of 1,200 respondents will be selected randomly, with proportional representation from each zone. This approach ensures comprehensive geographic coverage.

Data Collection Tools

A structured questionnaire (administered via both physical forms and online forms). Anthropometric measurements (weight, height, BMI, waist circumference, hip circumference, waist-to-hip ratio).

Variables Assessed Independent Variables

• Demographics: Age, gender, education, occupation, income, and socio-economic status. • Lifestyle factors: Dietary habits, physical activity, use of online food delivery platforms, and exercise frequency.

Dependent Variable: Body Mass Index (BMI).

Process

The questionnaire will be pre-tested on 20 respondents to ensure reliability and validity. Data will be collected both physically and digitally to maximize participation.

Statistical Analysis

Software: Statistical Package for the Social Sciences (SPSS), Version 20.

Techniques Descriptive Statistics

Frequencies, percentages, and means to summarize demographic and lifestyle data.

Inferential Statistics

• Chi-Square Test: To assess the relationship between categorical variables (e.g., socio-economic status and BMI). • Regression Analysis: To identify predictors of obesity.

• t-Tests/ANOVA: To compare mean differences in BMI across demographic and lifestyle variables.

Results and Discussion

Barriers to Exercise

The most significant barrier is an unsuitable environment (33.6%), followed by busy schedules (13.9%) and laziness (13.1%). Health problems and lack of interest contribute less significantly but still represent notable factors (9.7% and 6.7%, respectively). Environmental and scheduling issues dominate as barriers to exercise, highlighting the impact of urban infrastructure and lifestyle on health behavior. These trends suggest that solutions like community exercise programs, workplace fitness initiatives, and accessible recreational spaces are needed.

Dietary Patterns

Vegetarianism is predominant (75.4%), followed by nonvegetarian (15.3%) and eggetarian (7.6%) diets. Only 1.8% of respondents follow a vegan diet. Food consumption trends include a preference for traditional meals but an increasing reliance on food delivery services, with 70% of respondents using such platforms. While the vegetarian diet remains dominant due to cultural factors, the rising use of food delivery apps reflects a shift toward conveniencedriven eating habits. This reliance on outside food could lead to higher calorie intake and lower nutritional quality, contributing to obesity. The study analyzed the association of various independent variables with BMI among adults in Ahmedabad city and revealed several significant findings. Socio-economic status (SES) emerged as a crucial factor, with higher SES groups showing a strong association with increased overweight and obesity prevalence. This trend reflects dietary and lifestyle shifts typically seen with economic development. Similarly, variables such as education, occupation, and income were www.extensionjournal.com highly significant in influencing BMI. Individuals with higher education levels, particularly graduates and professionals, exhibited higher rates of obesity, often attributed to sedentary lifestyles. Physical activity intensity was another significant variable, with moderate activity being the most common among respondents. However, higher activity levels were correlated with lower obesity prevalence. Family structure also played a role, as individuals from nuclear families showed a higher prevalence of obesity compared to those from joint families.

Dietary patterns, specifically irregular meal patterns and increased consumption of processed foods, were strongly associated with higher obesity levels. Finally, the lack of regular exercise emerged as a critical factor contributing to obesity, underscoring the importance of active lifestyles in managing weight effectively. These findings highlight the multifactorial nature of obesity and the importance of addressing both lifestyle and socio-economic factors in public health interventions.

Conclusion

This study highlights the significant prevalence of obesity among urban adults in Ahmedabad City, emphasizing the multifactorial nature of this public health challenge. The findings underscore the strong association between modern lifestyle factors-such as sedentary behavior, reliance on online food delivery services, and irregular dietary patternsand elevated BMI levels. Notably, socio-economic status, education, and occupation were found to be highly significant predictors of obesity, reflecting the urban paradox where economic advancement often leads to unhealthy lifestyle behaviors. The predominance of sedentary activity, minimal engagement in heavy physical activity, and barriers like unsuitable environments and busy schedules further exacerbate the issue. Additionally, the cultural inclination toward vegetarian diets is being overshadowed by the growing consumption of calorie-dense, processed foods facilitated by convenience-driven eating habits. Addressing obesity in Ahmedabad's urban population requires targeted interventions, including public health campaigns promoting balanced diets, active lifestyles, and awareness of the risks associated with sedentary behavior and processed food consumption. Strategies such as community exercise programs, improved urban infrastructure to support physical activity, and workplace wellness initiatives can play a pivotal role. Furthermore, educating individuals about mindful eating and the importance of regular physical activity is critical. This research provides valuable insights for policymakers and healthcare professionals to design and implement effective obesity prevention and management strategies tailored to the urban context. By addressing both lifestyle and socio-economic determinants, these initiatives can significantly mitigate the rising obesity trend and its associated health risks, fostering a healthier urban population in Ahmedabad.

References

1. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004;79(3):379-384.
2. World Health Organization. Obesity and overweight; c2021. Available from: https://www.who.int/news-room/factsheets/detail/obesity-and-overweight. Accessed 2024 Dec 8.
3. Ahmedabad Smart City Mission. Overview of the Smart City Mission. Available from: https://smartcities.gov.in/. Accessed 2024 Dec 8.
4. National Family Health Survey (NFHS-5). Key indicators; c2019-2021. Available from: http://rchiips.org/nfhs/. Accessed 2024 Dec 8.
5. Popkin BM. Transitioning from the nutrition transition stage to a healthy lifestyle. Public Health Nutr. 2012;15(1):01-07.