https://orcid.org/0000-0002-4653-2489
ABSTRACT
Among many Asian countries, Pakistan is also facing an increase in overweight/obesity rate as an epidemic. This research explores how various built environment, personal, religious, cultural, and socioeconomic factors work differently for both sexes to contribute to increasing the Body Mass Index of female adults in all three Socioeconomic Statuses of the megacity Karachi, Pakistan. 210 random samples of 20 years or older male and female adults were selected, and the sample data, from survey questionnaires, was analyzed through Ordinary Least Square Regression in SPSS V.25. The results confirm that low-density neighborhoods, higher fast-food restaurant density, accessibility (walking distance in no. of min) to parks/playgrounds, household size, obesity running in the family, health condition of an individual, and discouraging behavior by others are positively associated with higher BMI. Whereas less junk food consumption in a week and availability of pleasant surroundings where people prefer walking are negatively associated with higher BMI. Although religious factors were not found connected to higher BMI, cultural, built environment, and religious factors combined were responsible for the choice of Physical Activity in both sexes. Walking was the most common whereas cycling was the least common PA in females in all SES.
Background
Developed vs developing countries – The case of Karachi, Pakistan
‘Overweight and Obesity’ rates have consistently been climbing for both developed and developing countries over the last three decades. The study on global, regional, and national prevalence of overweight and obesity in both adults and children confirms that the overweight and obesity rate increased from 28.8% to 36.9% in men, and from 29.8% to 38% in women for 188 countries between 1980 and 2013 (Ng et al. Citation2014). According to the above-mentioned study, the overweight rate was 27.9% for adult males and 38.4% for adult females, whereas the obesity rate was 14.4% for adult males and 14.3% for adult females. Although current data shows that overweight and obesity rate is higher in economically developed countries compared with developing countries, 35.2% vs 19.6% and 20.3% vs 6.7%, respectively, in 2005, it is also established that a greater number of people received its burden in developing nations due to rapid increase in urbanization, urban population, globalization and change in individual’s lifestyles. Various studies also suggest that this rising trend varies across different age groups, genders, races/ethnicity types, education levels, and socioeconomic classes (income level) (Gordon-Larsen et al. Citation2006). In 2008, the estimated annual medical spending on obesity was around 147 billion US $ for the United States only ($1,429 higher than those of normal weight) (Finkelstein et al. Citation2009). This spending on obesity-related illnesses surpasses drinking or smoking-related illnesses (Sturm Citation2002).
Pakistan, along with other Asian countries (see ), is also facing an increase in the overweight and obesity rate as an epidemic (Tanzil and Jamali Citation2016). This study indicates an increase in overweight and obesity rate in all age groups in Pakistan. According to their findings, women (adults) and girls (children) are more likely to be overweight and obese as compared to men (adults) and boys (children) in Pakistan. Another study compared the heights and Body Mass Index (BMI) of adults and children of both sexes in 600 households in three socioeconomic classes (high-income, middle-income, and low-income) for Karachi urban areas, also concludes that the women’s tendency of being overweight/obese increases with their age and uplift in socioeconomic status (Hakeem Citation2001). Although there is no state/provincial data available that would confirm the accurate figures for the difference in overweight and obesity rate in both genders, a general perception about the lifestyle, behavior, and social setup of the majority of women helps us understand that women are more likely to be overweight and obese based on the existing social, cultural, religious, and socioeconomic setup in Pakistan.
Table 1. Overweight/Obesity comparison between men & women in selected Asian countries as of 2013.
Mega-city ‘Karachi’ in Pakistan is home to more than 23 million people and has witnessed rapid urban sprawl since the 1980s because of migration and natural disasters in other parts of the country (Amer et al. Citation2013). Forbes in its 2013 report placed Karachi at the top position for all cities with the highest population growth rate (Kotkin and Cox Citation2008). Karachi is a magnet city where rural to urban migration is a primary reason for inevitable urban sprawl. The city expanded beyond its operational capacity to serve the huge addition of the population comprised mostly of the poor. According to the ‘World Population Review’, Karachi is growing at 5% annually which is twice the national growth rate (Karachi Strategic Development Plan Citation2020, 2007). A recent Japan International Cooperation Agency (JICA) report on South Asia (Citation2017) informs that 50% of Karachi’s population is living on less than 1.90$ a day (Activity Report South Asia Citation2017). Pakistan is a country with a Muslim majority population of around 96.4% where the male and female population is almost equal (In the 15-24 years group for every 1 female there is 1.07 male(s) and in the 25-54 years group for every 1 female there is 1.08 male(s)Footnote1.
Gender, culture, and religion
Being overweight and obese are directly linked with cardiovascular disease, hypertension, type 2 diabetes, stroke, arthritis, and certain forms of cancer (Must et al. Citation1999, Patterson et al. Citation2004, WHO Citation2013, Moreno and Sipress Citation1999, Mannino et al. Citation1980, Taylor et al. Citation2012); therefore, it is extremely necessary that both women and men equally participate in any form of physical activity (PA) including exercising, walking, and running. Globally, women’s participation in sports and PA is not equal and male participation is very dominant (Acosta and Carpenter Citation2004, Gill and Kamphoff Citation2010, Deaner and Smith Citation2012). As adherent to the Muslim faith, women are required to observe modesty in both clothes and social conduct, perhaps more than men (Boulanouar Citation2006). Although various Islamic communities differ in their treatment of women from extremely conservative to somewhat flexible approaches allowing women to hold an equal position in society, an inherent right given to them by the holy book ‘Quran’ (Surat-un-Noor in verses 66 to 69 explains about Muslim woman’s dress code and modesty) (Ali Citation2001) and teaching of the last prophet Muhammad (Benn et al. Citation2012). But the interpretation of Islamic teaching and beliefs by some religious clerics differ from each other and some strictly forbid women to wear tight clothes, expose their body parts and perform PA whether it be a sport, a PA, or any type of dance. On the other hand, there are other discriminatory challenges at the international level faced mostly by Muslim women such as banning the Iranian women’s team from a pre-Olympic qualifying match FIFA (the international football association) in June 2011, which targets their attire and observance of the hijab (head scarf) (Another FIFA fiasco, Citation2022).
Like many other Muslim countries, Pakistan is also considered a predominantly male-oriented society where women are not only less independent but also less self-sufficient in going out and performing various social, physical, educational, and work-related activities. There is strong evidence of several neighborhoods, especially in middle-income and low-income areas in Karachi and other parts of the country, where women mobilization is very limited; and they are not seen in parks and playgrounds working out or doing leisure activities. Observing the veil, going outside without a ‘mahram’Footnote2 and the requirement of wearing modest clothes (Badawi Citation1980) are some of the religious factors which play an important role in determining the PA by women. Therefore, one can assume that these cultural and religious boundaries may hinder women’s PA including exercising, walking, and running especially in conservative neighborhoods belonging to middle-income and low-income socioeconomic classes where more stringent religious and cultural beliefs are followed. There is another planning practice observed in most city neighborhoods where masjids (mosques) and madrasasFootnote3 are spatially connected with parks and playgrounds, and these open spaces are fully occupied by men because of their required visit to the masjid; when the call for prayers is made. During two of the prayers ‘Asr and Maghrib’, (the timings fall between 4 pm and 8 pm, and varies based on seasonal change), a peak time when the majority of people visit parks and playground, many are dominated by males with no traces of women. This trend indicates the dominant and biased behavior in using open spaces and parks in this study area.
Built environment, socioeconomic status, and individual behavior
Gender is not the only characteristic associated with less or more PA, instead, various empirical studies suggest that PA is also significantly limited by race/ethnicity and socioeconomic status/class. Various studies link ‘socioeconomic status’ with access to open spaces/parks/playgrounds/recreational facilities. Disparities and unequal access to these facilities may contribute to higher obesity rates in low-income areas or neighborhoods. Gordon-Larsen et al. performed an 8.05-km buffer around 42,857 census-block groups (19% of US block groups) and concluded that neighborhoods in low-income and minority areas do not possess the same physical environment facilities such as parks, playgrounds, and walkways as the other high-income neighborhoods have; which in turn lead to unequal distribution of built environment related illnesses such as asthma, overweight and obesity (Gordon-Larsen et al. Citation2006). In the case of United States, these low-income areas are mostly found situated close to highways and high traffic zones and are exposed to more air pollution, as well as have a higher tendency of diseases like asthma. Using public transit more often causes more pollution exposure and pedestrian fatalities (Mannino et al. Citation1980). Frumkin in his book establish that the pedestrian fatalities from 1994 to 1998 in Atlanta were more for African Americans and Hispanics than for Whites (9.74 per 100,00 for Hispanics, 3.85 for African Americans, and 1.64 for Whites) (Frumkin Citation2002). Moreno and Sipress (Citation1999) mention a similar pattern in the case of Virginia suburbs of Washington DC where Hispanics only constituent 8% of the population but have 21% of pedestrian fatalities. In the case of the sample data, the study finds a similar trend where 54% (M) and 57.5% (F) in low-income, 42.8% (M) and 22.8% (F) in middle-income and 22.2% (M) and 24% (F) in high-income neighborhoods have reported traffic is a major hindrance in performing PA outside [see ].
Table 2. Socioeconomic/Demographic characteristics and weight profile data of 20 years and older adults from six neighborhoods of three SES in Karachi Pakistan (2019).
Table 3. ‘Built Environment’, ‘Personal’, ‘Cultural’, and ‘Religious’ factors explaining higher BMI in males VS females, 20 years, and older adults from six neighborhoods of three SES in Karachi, Pakistan (2019).
According to CDC (Centre for Disease Control and Prevention) definition, ‘built environment’ refers to all the developments in neighborhoods used to live and work, and play, like buildings, homes, streets, open spaces, amenities, and all other infrastructure. Density, connections, proximity, access to facilities/food outlets, and travel mode/patterns are some important factors we discuss when we associate built environments with health outcomes. Many researchers argue that the concept of ‘Smart Growth’ i.e. mix land use (residential, commercial, retail, agricultural, industrial, etc.), greater density, and less sprawl, is beneficial for individual’s health because it promotes more walking, transit use and and decreases vehicle miles travel, as well as encouraging lower automobile dependency and ownership. Whereas greater urban sprawl encourages to depend more on automobiles than walking or bicycling and requires longer trips to travel from home to work/school/markets and other locations. Often, public transit is not available or feasible for low-density development/neighborhoods; therefore, greater urban sprawl forces individuals to travel more by automobile than to walk or bike small distances.
Genetics, personal choices, behaviors, and environment all have strong impacts on increasing overweight and obesity, but the alarming rate of this increase cannot be explained by these factors only (Evenson et al. Citation2016). This explains the importance of exploring various built environment factors which have a great influence on an individual’s lifestyle, physical activity, personal choices/behaviors, and food intake habits. A neighborhood’s ‘food environment’ is usually created by the design of the built environment. Proximity and density of supermarkets, grocery stores, and restaurants including fast food and others may dictate how an individual will respond to his dietary requirements and choices (Troped et al. Citation2013, p. 756). Individuals living near restaurants are more likely to consume fast or unhealthy food and have an obesity rate higher than individuals living close to grocery stores/supermarkets that are more likely to consume healthy food (fresh food with low fat, vegetables/fruits) (Larson et al. Citation2009). Although some studies suggest that being in proximity of supermarkets or grocery stores does not guarantee that people will be consuming fresh and healthy food (Gustafson et al. Citation2012). There are accessibility and several other problems associated with this theory, for example, how do we set an appropriate threshold distance to supermarkets, how do we take an appropriate boundary type and how do we measure accessibility as it depends on various factors including car ownership, socioeconomic status, etc.
Moreover, other studies have also determined that higher fast-food restaurant density and less physical activity is significantly associated with higher obesity rates. For 2010-12 data on New York students’ higher fast-food restaurant density was significantly associated with higher obesity rates (Dwicaksono et al. Citation2017). In the case of Karachi, Pakistan, and other urban areas of developing nations, the mushrooming of fast-food chains since the 1990s resulted in people consuming more junk food now than ever before. Moreover, developing nations are predicted to have a larger population size with overweight and obese people from 2005 to 2030 (Kelly et al. Citation2008) leading to more people in developing countries consuming relatively more junk food in the future. The sample data also suggest that as the density of restaurants (fast food and others) increases in a neighborhood people are more likely to consume it at least once a week (which exceeds as many as seven times a week) and this trend is consistent in all SES with a little variation [see ]. People are surrounded by a vast majority of fast food and other types of restaurants, especially people living in high-density neighborhoods, which makes it extremely convenient for them to access processed food.
Pakistani cuisine including the fast-food diet uses plenty of oil, which is the main reason for weight increase and a prime cause of obesity-related diseases like high blood pressure, and cardiac and stomach-related issues (such as ulcers). As the data indicates that 50% (M) and 44.2% (F) in low-income, 40% (M) and 34.2% (F) in middle-income and 58.5% (M) and 35.7% (F) in high-income neighborhoods consume fast food or high-calorie diet at least once (or more than once) per week. A vast majority of the study participants i.e. 47% (M) and 52% (F) of the total sample have serious health conditions such as high Blood Pressure, Diabetes, Tuberculosis, Joint pain, Thyroid, Back-ache, Ulcer, Cardiac and Respiratory problems, Arthritis, High Cholesterol, Hypertension, Hepatitis B, Anemia, Hernia, Eczema/Skin problem, Cervical Problem. Three out of 49.5% of study participants also reported terminal illnesses such as Breast Cancer, Kidney, and Brain Tumor.
The subjective nature of some factors in the built environment for example walkability or cycling in certain neighborhoods is more or less common due to cultural, environmental, social, and socioeconomic factors. Various built environment factors including access to parks/playgrounds/gyms/recreational centers, conditions of walkways/trails, conditions of streetlights/street signs, and the overall environment of surroundings determine whether people perform PA outdoors (Humpel Citation2002). In the sample data, 68.3% (M) and 80.64% (F) preferred walking over other types of PA (Exercise, yoga, swimming, aerobics), because it is comparatively less time-consuming, easy to perform, and requires no extra money/time for traveling. Cycling in the sample neighborhoods was not very common due to built environment and cultural factors and none of the woman samples reported it as a preferable PA in all SES. A headline was made in a local newspaper: ‘Women who dare to bicycle in Pakistan’, where a low-income neighborhood of ‘Lyari Town’ was recorded to have an unusual bicycling activity by girls on the road (Hadid and Sattar Citation2019).
Also, from the sample data, it was quite evident that low-income and high-income neighborhoods are consistent in availability/unavailability of the built environment features such as parks, playgrounds, and condition of sidewalks/trails as compared to middle-income neighborhoods where there is a varying trend. In the low-income neighborhoods ‘New Karachi and North Karachi’ and ‘Korangi-6’, 97.3% (M) and 100% (F) reported missing walkways and trails, whereas in high-income neighborhoods ‘DHA-VI’ and ‘Zamzama’, the figure was 8.9% (M) and 12% (F). In the Middle-income neighborhoods ‘Gulzar e Hijri Sector 19-A (TS)’ and ‘Gulshan e Iqbal Bl 13-C & Bl-16’, 65.8% (M) and 62.9% (F) reported missing walkways and trails.
Methodology
Study area and survey design
Megacity Karachi is divided into 18 Towns and 178 Union councils (the equivalent of a US County) [see ]. The estimated current population exceeds 23 million people with a population density of 63,000/sq. miles (Amer et al. Citation2013). In the first round, a list of large towns or counties (such as Gulshan-e- Iqbal town, Korangi, DHA, F.B. Area) was prepared while randomly selecting a few small neighborhoods from each town. In the second round, these neighborhoods were shortlisted into a set of two for each SES provided the survey response is good. In some cases when the survey team did not a get good response from a randomly selected neighborhood, they discontinued and reselected another neighborhood in proximity where they had a satisfactory survey response. At least two neighborhoods were randomly selected from each socioeconomic class with 50 random samples of 20 years or older male and female adults from each neighborhood (see ). A total of 300 surveys were again randomly selected to strike a balance between male and female participants and reduced to a total of 210 samples, 70 from each socioeconomic class omitting surveys with incomplete information. The samples had gender profiles of 52.8% (M) and 47.2% (F) in low-income neighborhoods, 50% (M) and 50% (F) in middle-income, and 64.3% (M) and 35.7% (F) in high-income neighborhoods (see ).
Figure 1. Karachi Township Map. Source: Karachi City Town Map (https://www.arcgis.com/apps/View/index.html?appid=67ec1d71f3a040db86e9df23eae6e0bd).
Figure 2. Karachi map with selected neighborhoods from each SES in Karachi Pakistan. (Source: Google Earth Engine Citation2019). HI-1 (a) High-Income 1 – Zamzama Park; HI-2 (b) High-Income 2 – Hilal Park DHA Phase VI; MI-1(c) Middle-Income 1 – Gulzar e Hijri Sector 19-A (TS) Park; MI-2 (d) Middle-Income 2 – Gulshan e Iqbal Bl-16 Park; LI-1 (e) Low-Income 1 – Korangi 6 (No Park); LI-2 (f) Low-Income 2 – North/New Karachi Park.
Although the study requires randomly selecting the study participants, the focused group was adults who fall in the overweight/obese category; therefore, a large amount of the sample data comprises males and females who are overweight or obese. Since the study was designed to find out the underlying factors (‘built environment’, ‘SES’, ‘personal’ ‘cultural’ and ‘religious’) behind the increase in the overweight/obesity rate, it was of utmost importance that participants who show signs of having higher BMIs must be selected. While selecting the neighborhoods the focus was to maintain a mix of low-density (suburban) and high-density areas (urban), although after huge urban sprawl it is difficult to define the urban-suburban boundary. Both low-income neighborhoods are high-density areas, one of the middle-income is high-density while the other is a low-density neighborhood, and both high-income neighborhoods are low-density areas (comparatively) [see ]. The reliable indicator considered in this study to estimate the socioeconomic status (SES) was the ‘plot/yard size’ of a neighborhood. Low-income neighborhoods generally have smaller yard sizes and are dense too, meaning there will be more people living in low-income neighborhoods if we draw a same-size radius around any park in neighborhoods of different SES.
Dependent variable (Y)
Body Mass Index (BMI) was the outcome variable for study participants (adults male/female, 20 years and over). BMI was calculated (in kg/m2) from self-reported height and weight using the CDC BMI calculator. The sample data was classified into four categories of weight profile, namely: underweight (BMI <18.5), normal weight (BMI 18.5-24.9), overweight (BMI 25.0-29.9), or obese (BMI >30). Overweight was referred to as BMI >85th < 95th percentile and obesity as BMI ≥95th percentile.
Independent variables (Xs)
The built environment, personal, religious, cultural, and socioeconomic variables were included as independent variables (Xs). The ‘Built Environment’ variables include the level of density (low density and high density), accessibility to parks/playgrounds (no. of minutes walked), accessibility to gyms/recreational centers (no. of minutes walked), condition of sidewalks/trails, presence of pleasant surroundings, neighborhood safety (in terms of the walking), presence of stray dogs, presence of annoying men/strangers/drug addicts, traffic problems, condition of streetlights and street signs, and no of fast food/other restaurants in proximity (see ).
‘Socioeconomic’ and ‘Demographic’ variables include socioeconomic status (which decides the category of neighborhoods i.e. high, middle, and low income), age group, marital status, education, ethnicity, family setup (combined or separate), and household size (see ).
‘Personal’ variables include physical incapability/health condition/prohibiting disease, overweight/obesity run in the family (genetically transferred), smoking, discouraging behavior by others, restrictions by others/no independence to go out, too shy to face others (women), tiredness, no motivation, afraid of injury/any situation, no interest in physical activity/exercise, weather severity (prevents going out for a walk), time availability (due to family responsibilities/education/job), family/friends exercising regularly in your family (have psychological effects), affordability problem, owning or personal car and walking for public transport (see ).
‘Religious’ and ‘Cultural’ variables include any type of religious issue such as veil observance, gym/parks used by both genders, conservative families, restrictions on attire, etc (see ).
Survey questionnaire and variables
‘Survey Questionnaires’ were composed of two sections identifying: 1) Anonymous personal (demographic), socioeconomic, and household information, 2) built environment/neighborhood, personal, religious, and cultural information, including ‘Yes/No/Concerns’ questions. Questions related to socioeconomic data may overlap in these two sections (see supplemental data).
Demographic and household information
The first section elicits demographic data on sex (referred to as gender in most of this paper), age, language, race/ethnicity, education level, job title, neighborhood name (SES was identified based on this information), family size and setup, personal income, family aggregated/combined income, marital status, and self-reported weight (kgs.) and height (m) to calculate individual’s BMI.
Statistical analyses
Ordinary least squares (OLS) models were used to examine the relationship between the Body Mass Index (BMI) as the dependent variable (Y) and the built environment, personal, religious, cultural, and socioeconomic factors as independent variables (X’s). SPSS Statistics V. 25 was used to analyze the data variables. Descriptive statistics (means, standard deviations, max, min, and range) were calculated [see ]. While running the OLS regression model, variables with P > .05 were removed and the final model was rerun including only significant variables to assess independent effects.
Results
Descriptive statistics
shows the study’s descriptive statistics for all study participants. The mean age is 37.26 years (SD 12.96), the mean weight is 88.90 kg (SD 18.84), the mean height is 1.65 m (SD 0.10), and the mean BMI is 32.58 Kg/m2.
Table 4. Descriptive statistics of adults from six neighborhoods of three SES in Karachi, Pakistan (2019).
Linear regression results
From ordinary least squares model findings, the study reveals a strong relationship between the Body Mass Index (BMI) of individuals with their socioeconomic status (SES), built environment, and personal factors (see ). With the socioeconomic status increase, the tendency of being overweight/obese decreases. The high and middle-income SES was significantly associated with lower BMI (b = −6.481and b = −3.633, respectively; p < .01). Although there was no significant association found between gender and BMI from OLS regression models, being a female increases average BMI by 1.07 than being a male. The other findings from OLS models also seem to be consistent with existing literature. Low-density neighborhoods are significantly associated with higher BMI (b = 5.863; p < .01) as well as higher fast-food restaurant density was significantly associated with higher BMI (b = 0.078; p < .01). Less junk food consumption in a week is negatively associated with the higher BMI (b = −0.715; p < .01).
Table 5. Significant independent variables contribution to BMI.
Accessibility (walking distance in no. of min) to parks/playgrounds was significantly associated with higher BMI (b = .160; p < .01). The longer it takes to reach a park/playground the lower the possibility of Physical Activity (PA), which significantly increases the possibility of having a higher BMI. Pleasant surroundings of a neighborhood were negatively associated with higher BMI (b = −4.064; p < .01), suggesting people prefer to walk in neighborhoods with pleasant surroundings, potentially helping to lower BMI in adult males and females. Household Size (b = 0.422; p < .01) was also significantly associated with higher BMI. It indicates that living in larger households makes it difficult to perform PA and consequently people in larger households tend to have higher BMI than smaller households. Obesity running in the family was also positively associated with higher BMI (b = 2.251; p < .05). Health condition of an individual was also positively associated with higher BMI (b = 2.382; p < .01); adults having different types of health condition have double the tendency of having higher BMI. Discouraging behavior by others was also positively associated with higher BMI (b = 3.521; p < .01).
Discussion, conclusion, and recommendations
Physical Activity (PA) has been considered a necessary measure to improve the overall health of communities and individuals in all age groups. According to WHO data, 31% of adults (15 and above) were insufficiently active in 2008 (28% men and 34% women) causing 3.2 million deaths each year due to insufficient physical activity (WHO Citation2013). Along with WHO findings, many other studies have revealed that this participation is highly unequal in both sexes with female participation more suppressed due to various reasons. Socioeconomic factor plays an important role where low-income/high-poverty areas face various forms of disparities including unjust policies and practices leading to an inequitable distribution of open areas such as parks/playgrounds (Gordon-Larsen et al. Citation2006, Evenson et al. Citation2016).
This study builds on the assumption that socioeconomic status, built environment, and personal, cultural, and religious factors have strong impacts on increasing overweight/obesity rates, especially in women. Although the study did not find a striking difference in overweight/obesity rate between men and women, the sample data indicates that women have a little more tendency of being overweight/obese than their male counterparts. Gender and SES-related disparities in the built environment contribute negatively to overall people’s health specifically for women. Surprisingly, religious factors were not found connected to higher Body Mass Index (BMI) in women but built environment, cultural, and religious factors combined were responsible for the choice of PA in both sexes. Walking was the only common PA observed in females, whereas cycling was the least common PA in all 3 socioeconomic statuses (SES) in both sexes.
From sample data, 68.3% (M) and 80.64% (F) reported that they prefer to walk in the neighborhood parks as it saves both their time and the cost involved in other types of PA. Sports and other forms of rigorous exercises such as swimming and running are not found as common in women as it was reported in men. A small percentage of women from middle-income and high-income neighborhoods also like to perform yoga and aerobics. Religious factors, unexpectedly, were not significant in explaining the increase in overweight/obesity as only 8.1% (M) and 27.2% (F) from low-income neighborhoods, 5.7% (M) and 0% (F) from middle-income, and 8.8% (M) and 12% (F) from high-income neighborhoods reported that they have certain religious issue/s in performing PA outdoor. This might be explained by the fact the selected neighborhoods (especially from low-income SES) may have been comparatively less conservative in their religious beliefs as compared to others. Personal factors, such as time availability, weather severity, and tiredness were also reported as important issues which prevent people in all three SES and both sexes from performing any PA outdoors [see ].
Neighborhoods from all three SES consistently reported robbery and safety in their surroundings as recurrent issues. Pleasant surroundings in neighborhoods support people’s PA outdoors and are negatively associated with higher BMIs. Low-income neighborhoods reported an absence of pleasant surroundings as 97.3% (M) and 100% (F) confirm that they have unpleasant surroundings which prohibit them to go outside and perform any PA consequently increasing overweight/obesity rates in both sexes. Low-income and high-income neighborhoods were more consistent in the availability/unavailability of the built environment features such as parks, playgrounds, and condition of sidewalks/trails as compared to middle-income neighborhoods where there was a varying trend witnessed (see ). This corroborates that disparities in the built-environment features such as parks, playgrounds, sidewalks, and trails are a major issue that contributes to the increasing overweight/obese rates in low-income neighborhoods. Comparing low-income neighborhoods where 97.3% (M) and 100% (F) to high-income neighborhoods where only 8.9% (M) and 12% (F) reported missing walkways and trails validates that low-income neighborhoods are deprived of basic facilities such as parks/playgrounds (see ). In the case of the middle-income neighborhoods, 65.8% (M) and 62.9% (F) reported missing walkways and trails, indicating no consistency in built environment features among various middle-income neighborhoods. For example, one middle-income neighborhood in the sample data has parks, playgrounds, sidewalks, and trails, all in good condition, whereas the other is missing these features altogether (see )). People from low-income neighborhoods also reported broken sewerage lines, open dumping as well as affordability problems (buying trade mills or getting admission in the gym) as major hindrances in performing any type of PA indoors/outdoors.
Figure 3. HI-1 & 2-Zamzama Park and Hilal Park (DHA Phase VI) MI-1 & 2-Gulzar e Hijri Sector-19 a (TS) Park and Gulshan-e-Iqbal Bl-16 Park and LI-1 & 2-Korangi 6 (no Park) and North/New Karachi Park.
The data also suggested a strong relationship between some built environment factors such as the density of restaurants (fast food and others), personal factors such as fast-food consumption in a week (which exceeds as many as seven times a week) as well as sedentary lifestyle contributing increasing overweight/obesity rates in both sexes and all 3 SES with a little variation [see ]. It is also alarming that a vast majority of overweight and obese people are suffering from one or more than one chronic health conditions. From the sample data, 47% (M) and 52% (F) of all study participants very commonly reported various health conditions including high BP, diabetes, joint pain, backache, high cholesterol, hypertension, and cardiac and respiratory problems. 2.8% of 49.5% of study participants also reported terminal illnesses such as breast cancer, kidney, and brain tumor. Culturally, smoking is predominantly a trait fixed to only men, as for women it is more of a stigma than a health concern. Only two female study participants (6%) from low-income neighborhoods confide that they smoke occasionally and in solitude.
From a policy and administrative perspective, Karachi city parks/playgrounds are operated by local authorities like DHA (Defense Housing Authority; created in the 1960s and controls and maintains their land), KMC (Karachi Municipal Corporation; controls the land uses, now abolished), DMC (District Municipal Corporation; responsible for maintenance). According to standards specified for residential land uses in ‘Karachi Building and Town Planning Regulations’, there should be the provision of parks/playgrounds in a residential scheme of 2.5 acres or greater (Citation2002). Clause No. 20-4.1.3 (b) on page no. 238 states that there should be at least 8% (revised in 2005, previously was 5%) of the land reserved for parks/playgrounds based on a residential schemes area (Building and Regulations Citation2002). If a neighborhood is smaller in size (which is the case with many low-income housing schemes), for example, 5 acres, the parks/playground area would be around 0.40 acres which is considered quite low compared to the standards in developed countries. In comparison to the US, a national survey (a report by ‘Trust for Public Land’) suggested that park space per capita ranged from 2.7 acres per thousand residents in Fresno to 46.8 acres per thousand residents in El Paso, whereas the national average is 15.8 acres per thousand residents although there is no national standard exist in case of United States (Harnik Citation2002).
Due to the unproportioned distribution of open spaces among all SES, low-income neighborhoods have smaller parks/playgrounds than middle and high-income neighborhoods, which in turn causes these parks to have no or little provision of various park amenities such as playgrounds, play areas, sitting areas, etc. Along with park-covered area, the quality of spaces in those low-income parks is also compromised as broken equipment and lack of maintenance is very common. The majority of low and middle-income parks/playgrounds are missing sports fields, and areas supporting sports activities related to youth, especially for girls (such as skate stations, tennis courts, etc.), as compared to high-income parks/playgrounds. On the other hand, male children and youth are commonly found playing on pathways in parks, streets, or any available open grounds. In addition to this, another important planning practice of residential land use that is evident in many housing schemes is to have a center of land parcel and locate amenities like parks/playgrounds, mosques, schools, and commercial areas within the center. (Building and Regulations Citation2002) Most of the housing schemes were essentially designed to have mosques either in the center or adjacent to these housing schemes which hinder women’s participation in PA or sports when the parks/playgrounds are overly occupied by men during the peak hour of park use coinciding with the waiting period between two prayers “Asr & Maghreb”.
This study suggested that both spatial (such as availability, accessibility, and equitable access) and non-spatial factors (such as parks/playgrounds quality of spaces) are crucial for increasing physical activity and optimal park use by both sexes, especially for women. Close observations reveal that in many cases non-spatial factors are more responsible for park visitation and PA by females than non-spatial factors. For example, the smaller parks may witness more people of all age-group and sexes provided the quality of the park and its physical infrastructure is in good condition. Quality of spaces in parks/playgrounds also relates to safety and perceived safety, a major indicator of women’s use of urban open spaces (Bedimo-Rung et al. Citation2005).
Cultural practices and religious beliefs also hold a very strong impact on how women and girls use parks/playgrounds based on how conservative a neighborhood is. Culturally, women and girls face more constraints on their freedom of movement in general. In many conservative neighborhoods, a very strict dress code/veil is usually observed among many adult females and young girls, which may be a hindrance to engaging in any rigorous PA. For example, a few females discuss how walking with their veils and scarves on in very hot temperatures makes it a difficult task to perform. Therefore, many women who want to do a rigorous PA, do not do it in parks/playgrounds and instead resort to gender-segregated gyms and swimming poles. Some Parks also apply a ‘family-only’ entry policy where no man can enter the facility without a family/woman/child. Even some parks have exercised a stricter approach to gender segregation by allocating ‘female only parks’ (in local language it is called ‘pardah [veil] park’). The concept, though already in practice in a few parks, cannot be recommended until validated by the sufficient qualitative and quantitative body of research on actual benefits and women’s perception of these facilities.
In the absence of effective policies, governance, and community service by public departments, community organizations and non-governmental organizations (NGOs) often have a pivotal role to play particularly in a context of a developing country. Some local organizations are already running community programs that organize and support programs around physical activities/exercises/yoga classes, but these practices are unorganized and only offered at a few locations mostly in high-income neighborhoods. Systematically organizing and arranging these health awareness programs in low- and middle-income neighborhoods targeting young girls and women may benefit a large section of society as the majority of girls and women will be motivated, encouraged, and feel protected in the group activities as compared to going alone to perform any PA outdoors. Another recommendation is to allocate extracurricular activities (such as sports and PA) as a distinct discipline to school, college, and university bodies, specifically for girl students to promote their participation in organized sports-related activities. Also, orientation and career awareness programs in sports may benefit these girl students very early in their development stages. Lastly, neighborhoods at a community level may devise methods and programs to upgrade their walkways, open areas, and green spaces to provide a safe and pleasant environment for its inhabitants to enjoy a commonly performed PA, i.e., walking or jogging in the study area.
Considering the huge population size (estimated 23 million people), diversity of ethnicity and origin, and urban sprawl of the city; selecting two neighborhoods from each socioeconomic status (SES) and moderately small sample size (210 participants) may result in statistically significant and non-significant bias of some indicators. For example, expectedly in many low-income and middle-income conservative neighborhoods, cultural and religious factors may have a significant effect on women’s participation in PA outdoors which is likely to affect their BMIs. Due to varying trends in the built environment of middle-income neighborhoods, some built environment factors such as conditions of pathways and availability of parks/playgrounds may have statistically significant effects on BMIs based on the selection of neighborhoods. Also, the unavailability and inaccuracy of data on neighborhoods facing environmental injustice issues (such as the proximity of toxic environment of factories, exposure to open dumping of solid waste, and unavailability of health facilities and open spaces like parks/playgrounds, clean water, and sanitation) and selecting those neighborhoods may have statistically significant effects on BMIs of study participants.
However, in the case of personal factors (such as pre-existing health conditions, overweight/obesity running in the family, personal choices/preferences of people for doing PA outdoor/indoor, weather severity, and time availability) selecting two neighborhoods from each socioeconomic status (SES) and moderately small sample size, may not have statistically significant effects on the BMI of study participants.
Strengths, limitations, and challenges
The growing health concerns due to the increase in overweight and obesity worldwide, and the need to engage in PA and sports to promote a healthy lifestyle, substantiate the need to research various factors which affect people’s physical and mental health. This empirical case study that focuses on surveying people and the built environment provides evidence of the underlying issues and bring a comprehensive approach towards the understanding of various connected issues such as gender and health disparities due to SES difference; cultural, religious, and social contexts; as well as the impact of planning policies and practices on the people and spaces. This study provides a thorough understanding of how socioeconomic status affects the built environment of a neighborhood which in turn contributes to lower or higher BMIs in adults. Since this study also compares the personal, cultural, religious, and gender-specific attributes within these three socio-economic statuses, it helps to conclude that SES and built environment-related disparities play an important role in increasing overweight and obesity in adult men and women.
The unavailability of funding has made this study quite challenging in selecting a moderately large number of neighborhoods. Therefore, the limitation of the two neighborhoods from each SES may limit the generalizability of the results. In the future, based on the population size, diversity, and urban sprawl of the city; the sample size may be increased to at least six neighborhoods from each SES. The data was more conveniently obtained from middle-income neighborhoods than from low-income and high-income neighborhoods. People from middle-income neighborhoods were willing to provide the requested information readily, whereas in low-income neighborhoods and high-income neighborhoods the surveyor had to face some cooperation and comprehension challenges. At the policy and planning level, another limitation of this study is the challenge of implementing interventions at local and city levels because it involves astronomically large investments in terms of money, effort, time, creativity, capacity, competence, and evidence-based research.
Human subjects
The study (IRB201901537) was submitted for the University of Florida IRB review and obtained exempt from the institutional review board (with some changes requested by the exempt reviewer). The study (NBC-420 Exemption) also received permission from National Bioethics Committee (NBC) Pakistan.
Supplemental Material
Download PDF (102.8 KB)Acknowledgments
I convey my sincere gratitude to several people who helped me and guided me throughout the survey and research process including my Ph.D. advisors Dr. Timothy Murtha Dr. Christopher Silver Dr. Emre Tepe and Ms. Sanjeeda Shaheen the resource person who supervised data collection process from all the neighborhoods and all the study participants for their participation and timely cooperation.
Disclosure statement
No potential conflict of interest was reported by the author.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/23748834.2022.2155290.
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Afsheen Sadaf
Afsheen Sadaf received her Ph.D. in Urban & Regional Planning from the School of Landscape Architecture and Planning, College of Design, Construction & Planning at the University of Florida in August 2022. Currently, she is a Post-Doctoral Research Associate at the Department of Landscape Architecture & Planning at the University of Florida. Her research interests include Health & Built Environment, Health Inequalities (SES & Gender); Social and Diversity Planning/Social Inclusion/Equity; Sustainability and Environment; Coastal Resilience, and GIS. During her Ph.D. program, she was serving as a Graduate Teaching Assistant in the Department of Urban & Regional Planning at University of Florida. She has presented her research at various platforms including ACSP (Association of Collegiate School of Planning) and has earned the prestigious ACSP-FWIG Marsha Ritzdorf Award in 2020 for this case study research.
Notes
2. A male counterpart either husband brother son or a blood relative.
3. Mosque/Masjid/Madarsa - A ‘Mosque’ is a designated religious space specifically for Muslims (men). All Muslims (12 years and above) are required to perform mandatory prayers five times a day at specific times, and it is obligatory for men to pray at the mosque or masjid. In some cultures, women also become part of the congregation, especially during Ramadan and Friday prayers.
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