J Obes Metab Syndr 2020; 29(1): 58-66
Published online March 30, 2020 https://doi.org/10.7570/jomes19039
Copyright © Korean Society for the Study of Obesity.
Muhammad Asif1,* , Muhammad Aslam2, Saima Altaf2, Saima Atif3, Abdul Majid4
1Department of Statistics, Government Degree College, Qadir Pur Raan, Multan; 2Department of Statistics, Bahauddin Zakariya University, Multan; 3Department of Statistics, University of Sialkot, Sialkot; 4Pakistan Bureau of Statistics, Regional Office Multan, Multan, Pakistan
Department of Statistics, Government Degree College, Qadir Pur Raan, Multan 60000, Pakistan
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Keywords: Body mass index, Overweight, Obesity, Pakistani adults, Pakistan Panel Household Survey
Over the last few decades, evidence has strongly suggested that overweight and obesity have increased at worrying levels globally.1 Between 1980 and 2014, the obesity burden among adults grew to more than double. The prevalence of overweight and obesity is higher in women than in men.1,2 Due to the large prevalence, the World Health Organization (WHO) declared overweight and obesity as a global epidemic.2,3 At present, almost every nation is experiencing this situation, although to significantly varying degrees not only by nation and region, but also by race and ethnic group.3,4
Many developing countries such as Pakistan have been facing a dual challenge of having both underweight and excess body weight populations. Having excess body weight was once perceived to be a phenomenon of the developed world. However, in recent years, it has extended to developing countries. Now, the burden of overweight and obesity in developing countries, including Pakistan, has increased several-fold. In 2014, global disease estimates showed that Pakistan stands at number eight among the 10 countries hosting half of the 693 million obese individuals in the world.5
Body mass index (BMI), calculated as weight in kilograms divided by height in squared meters, has long been the accepted criterion used for body weight assessment of an individual. Usually, BMI cutoffs of 25.0–29.99 kg/m2 and ≥30.0 kg/m2 are used for classifying overweight and obese, respectively.3 Globally, various noncommunicable diseases (i.e., cardiovascular diseases, hypertension, type 2 diabetes mellitus, dyslipidemia, cancer) are associated with larger BMI, and a major share of these diseases are from developing countries.6
When considering the severe health hazards associated with overweight and obesity, it becomes necessary to study this health problem for a particular population. Various population-based epidemiological studies7-10 have been conducted on exposing the obesity issue in adults as a public health concern. However, in Pakistan, limited data exist showing the nationwide prevalence of obesity among adults. For instance, Jafar et al.11 used the data from National Health Survey of Pakistan (NHSP; 1990–1994) and reported that 25.0% of adults were either overweight or obese. These estimates based on NHSP data are now out-of-date and need to be recomputed. Moreover, massive changes in dietary intake patterns and an increasingly sedentary lifestyle distinguish normal weight adults from those that are overweight or obese. This fact also suggests that the overweight and obesity estimates of adults should be updated. We therefore designed the present work. The main objective of the study is to examine the current prevalence of overweight and obesity in the adult population of Pakistan. We also identify the potential sociodemographic factors that are associated with overweight and obesity.
Data from the Pakistan Panel Household Survey (PPHS-2010) were used for the attainment of this study’s objective. The PPHS was conducted as a joint project between the Pakistan Institute of Development Economics, Islamabad and World Bank to analyze poverty and social dynamics in Pakistan. In this multidimensional household survey, health-related information such as height and weight are available for both sexes and for every age group to complete a nutritional status assessment of the Pakistani population. However, only the data for adults (age 19 years or over) are of concern in this study.
This population-based household survey was conducted in 16 different districts of four major administrative units, or provinces, namely: Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan (Fig. 1). Further details about the sample size, sampling procedure, and design can be seen from an earlier report by Durr-e-Nayab and Arif.12 Here, however, we highlight some of the methods relevant to the current study.
Out of a total of 29,744 individuals surveyed, 10,063 adults were included in the present analysis. Missing observations (where height or weight were not available) and outliers (using box plots) were already excluded. Among the total study population (n=10,063), 3,755 individuals belonged to six districts of Punjab (Faisalabad [n=899], Attock [n=464], Hafizabad [n=607], Vehari [n=527], Muzaffargarh [n=517], and Bahawalpur [n=741]); 3,603 were from four districts of Sindh (Badin [n=1,558], Nawab Shah [n=878], Mirpur Khas [n=521], and Larkana [n=646]); 1,485 were from three districts of Khyber Pakhtunkhwa (Dir [n=826], Mardan [n=479], and Lakki Marwat [n=180]); and 1,220 were from three districts of Balochistan (Loralai [n=374], Khuzdar [n=411], and Gwadar [n=435]).
The study was approved by the Departmental Ethics Committee of Bahauddin Zakariya University, Multan, Pakistan (IRB No. SOC/D/2511/19). Informed consent was waived because researchers only accessed and analyzed the secondary data set. The authors assert that all procedures contributing to this work complied with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Data on demographics (age, sex, marital status, area of residence) and health-related variables (height [cm] and weight [kg]) were obtained from the above stated source. For the individual’s nutritional status assessment, the international cutoffs recommended by WHO were used in the study. These classifications of nutritional status assessment are as follows: BMI <18.5 kg/m2, underweight; 18.5≤BMI<25.0 kg/m2, normal weight; 25.0≤BMI<30.0 kg/m2, overweight; and BMI ≥30.0 kg/m2, obese.2,3
For primary statistical analysis, the prevalence of overweight and obesity were determined according to age, sex, marital status, and area. Some descriptive statistics (i.e., mean, standard deviation [SD], and centile values) of each quantitative variable were presented by sex and age group. sex-wise mean difference was tested using the two-sample t-test. The analysis of variance technique was used to identify any mean difference between the age groups in both men and women. Meanwhile, the Pearson chi-square test was used to determine the association between categorical variables. Furthermore, using univariate logistic regression, odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were estimated to evaluate the most important factors associated with overweight/obesity. For the logistic regression analysis, overweight including obesity (BMI ≥25.0 kg/m2) and obesity (BMI ≥30.0 kg/m2) were used as the dependent variables (i.e., overweight/ obesity=1 with normal weight=0 and obesity=1 with normal weight=0, respectively). All statistical analyses were performed using IBM SPSS version 21.0 (IBM Corp., Armonk, NY, USA), and a
A total of 10,063 participants (38.9% men and 61.1% women) were included in this study. The mean (SD) age of the participants was 38.20 years (15.67 years). More than two-thirds of the participants (68.8%) were young adults (i.e., 19–44 years of age), and a majority of the participants (71.9%) were married. The ratio of rural to urban residence was 2.68:1, where 72.8% were rural residents and 27.2% were urban. Compared to the urban participants, the rural participants were more likely to be older and married. Of the total of 10,063 participants, 2,296 (22.8%) were overweight, and 512 (5.1%) were obese (Table 1), and the mean (SD) BMI was 22.91 kg/m2 (3.89 kg/m2). Using a BMI of 25 kg/m2 as the cutpoint, the prevalence of overweight or obesity differed across sex (women vs. men, 30.2% vs. 24.3%), area (urban vs. rural, 31.0% vs. 26.7%), and marital status (ever-married vs. unmarried, 30.4% vs. 18.5%) (Figs. 2, 3). After applying the chi-square test, age and all previously-mentioned categorical variables were significantly (
Among both men and women, age-specific obesity prevalence increased until age 64 and declined thereafter. The obesity problem peaked for both women (10.2%) and men (4.4%) in the 55–64 age group. However, overweight prevalence was highest for women (29.9%) in the 35–44 age group, compared to being highest for men (27.6%) in the 45–54 age group (Fig. 2). Age-specific obesity trends according to residential area show that urban adults aged 55–64 years had a higher obesity prevalence than their rural counterparts (8.6% vs. 7.6%, respectively). For the other age-groups (except those 65 or older), overweight and obesity prevalence in urban residents were also higher than in rural residents (Fig. 2). The difference in percentage points indicates that the obesity threat is more serious in urban adults than in rural ones.
Sex- and age-specific descriptive measures (means, SD, and centiles) of BMI are presented in Table 2. The results reveal that women have significantly (
Estimated crude ORs, along with their 95% CI, representing the risks of being overweight and obese or exclusively obese are presented in Table 3. The results, which were derived from a logistic regression model, revealed that the risk of getting excess weight (i.e., BMI ≥25.0 kg/m2) increased until the age of 64 and decreased thereafter. Female participants were more at risk of excess weight (OR, 1.34; 95% CI, 1.23–1.47) than males. Moreover, ever-married (OR, 1.92; 95% CI, 1.70–2.16) and urban residential (OR, 1.23; 95% CI, 1.12–1.35) participants were also more likely to be overweight or obese as compared to unmarried and rural participants, respectively. Crude ORs for the risk of reaching obese status (i.e., BMI ≥30.0 kg/m2) showed that the risk was significantly higher in middle-aged adults (i.e., 35–64 years), women, ever-married individuals, and individuals living in urban areas.
Estimated crude ORs when the participants were stratified by urban and rural residence are displayed in Table 4. Middle-aged adults (compared to those aged 19–34 years: OR, 1.69–2.69; 95% CI, 1.25–3.77), women (compared to men: OR, 1.33–2.62; 95% CI, 1.14–3.89), and ever-married (compared to unmarried: OR, 1.70–3.24; 95% CI, 1.47–5.55) among both urban and rural residents were more likely to be overweight and obese than their counterparts. However, adults of urban residence had a higher risk of getting overweight and obese than rural adults. For example, the obesity ORs for women living in rural and urban residences were 1.80 and 2.62, respectively, indicating that women in urban residences had 0.82 times greater risk of getting obese than rural women.
Overweight and obesity are well-known health problems in every part of the world, with a prevalence among the adult population significantly varying from 15% to 60%.2,3 During the last two decades, Asian developing countries have become more vulnerable to this serious public health threat. Although there has been a need for updated population-based data on the prevalence of obesity among adults in Pakistan, few regional studies13-17 with adults have identified the escalating rates of overweight and obesity. We therefore established such a kind of study.
Our findings related to overweight (22.8%) and obesity (5.1%) are comparable with previously published research on Chinese populations.6,18,19 However, these prevalence rates were found to be higher in studies conducted in Canada,20 the USA,21 Greece,22 Korea, 23 Turkey,24 and England,25 which confirms the statement that obesity burden varies between countries due to socioeconomic and environmental changes (e.g., climate, diet, physical activity, etc.). Our results are also comparable with the earlier local literature; for example, an urban Karachi survey has shown a 28% prevalence of overweight/obesity, keeping a BMI of 25.0 kg/m2 as the cutoff point.17 Another study by Khan et al.13 reported an obesity prevalence of 4.8% for Balochistani adults; an obesity rate of 8.0% was also determined for Peshawari adults.14 A study reported 25.0% of adults in Pakistan were either overweight or obese.11 However, in this study, 23.0 kg/m2 was used as the cutoff point for an abnormal BMI. Some regional disparity in the prevalence of overweight (29.0%–46%) and obesity (20.8%–27.85%) was also seen among Pakistani adults.15,16 This disparity may be explained by varying ethnicities, age ranges, and the use of WHO-recommended BMI cutoff points for the Asia Pacific Region instead of the international cutoffs for defining obesity.
Our data showed that overweight and obesity were both highest among middle-aged adults (i.e., 35–64 years of age) and lowest in young Pakistani adults (i.e., 19–34 years of age). The rates were consistently higher in women when compared with men across all age-groups. Similar patterns were also observed in an earlier study from Pakistan.11 A few studies on Turkish,24 Iranian,8 and Omani26 adults reported the lowest obesity rates for those under 30 years of age and peak obesity between the ages of 30 to 60 years. A study of the Saudi adult population also yielded similar findings.27 In agreement with earlier studies,6,8,22,24,26,27 Pakistani women had a higher mean BMI than men and occupied more of the obesity burden than did men (e.g., in the overall sample, obesity rates were 6.3% in women vs. 3.2% in men). This may be due to the fact that women in Pakistan usually get married in their 20s. Therefore, being confined to the home after marriage and having less physical activity might be the major reason for weight gain. Similar to previous research, 13,27,28 we observed that ever-married Pakistani adults and adults living in urban areas were more likely to be overweight or obese than those living in rural areas. This is so because in Pakistan, lifestyles are blatantly different in urban and rural areas. Among urban people, a colossal change in nutritional habits and consumption of food has been observed compared to in rural people, and such a sedentary lifestyle may be less focused on attractiveness, leading to more weight gain.
Various published literature has explained that age and other sociodemographic variables such as sex, marital status, and residential area are the significant risk factors for overweight and obesity.8,11,13 Parallel to these, our results from logistic regression analysis exhibited that middle-age adults (35–64 years), female sex, married individuals, and individuals living in urban areas had higher risks of excess weight than their counterparts.
The International Obesity Task Force recommended that the 85th and 95th percentiles, corresponding to BMI 25.0 kg/m2 and 30.0 kg/m2, respectively, should be used as cutoff points for determining overweight and obesity, respectively, for the adult population. By considering the overall data in our study, a BMI of 25.0 kg/m2 also corresponds to the 85th percentile in both sexes, and a BMI of 30.0 kg/m2 corresponds to the 95th percentile in all women, while action level was low among men.
The major strength of this study was that the sampling design and sampling technique for data collection were robust enough to ensure representativeness of the population-based sample and external validity. This is due to the fact that a secondary data set from PPHS-2010 was used. On the other hand, socioeconomic status, diet, and physical activity are also potential risk factors for obesity, but such information was not taken into account in this research, providing a limitation of the study. Moreover, BMI is used for the diagnosis of obesity but cannot provide information about body fat; therefore, we were unable to classify overweight/obesity using body fat percentage as a metric. This fact also adds to the limitations of the present study.
This study reports the high prevalence of overweight and obesity in the Pakistani adult population. Within this population, middleaged (35–64 years) individuals are more likely to become overweight and obese. This risk is especially alarming among Pakistani women, married individuals, and individuals living in urban areas. These findings suggest that there is a need to avoid unhealthy lifestyle habits such as excessive eating and an energy-dense diet, sedentary behavior, and inappropriate sleep duration to improve adult health. Some health promotion programs should also be launched at the national level to decrease the possible epidemic of obesity and obesity-related chronic diseases.
The authors declare no conflict of interest.
The authors gratefully acknowledge Dr. Zamir Hussain (National University of Sciences and Technology, Islamabad, Pakistan), who greatly helped us by sharing the data set of the Pakistan Panel Household Survey-2010 in an SPSS file.
Study concept and design: MA (Muhammad Asif); acquisition of data: MA (Muhammad Asif) and AM; analysis and interpretation of data: MA (Muhammad Asif), AM and SA; drafting of the manuscript: MA (Muhammad Asif) and MA (Muhammad Aslam); critical revision of the manuscript: MA (Muhammad Aslam) and SA; statistical analysis: MA (Muhammad Asif) and SA; and study supervision: MA (Muhammad Aslam).
Distribution of sociodemographic and nutrition-related characteristics of the study population (n= 10,063)
|Age group (yr)||38.20 ± 15.67|
|≥ 65||800 (7.9)|
|Married/living with partner||7,236 (71.9)|
|Area of residence|
|Nutritional status||22.91 ± 3.89|
|Underweight (BMI < 18.5 kg/m2)||1,284 (12.8)|
|Normal weight (18.5≤BMI < 25.0 kg/m2)||5,971 (59.3)|
|Overweight (25.0≤BMI < 30.0 kg/m2)||2,296 (22.8)|
|Obese (BMI≥30.0 kg/m2)||512 (5.1)|
Values are presented as mean± standard deviation or number (%).
BMI, body mass index.
Descriptive measures of BMI among Pakistani adults
|BMI (kg/m2)*||19–34||22.15 ± 3.40||17.23||18.13||19.72||21.80||24.13||25.78||27.05||28.62|
|35–44||23.41 ± 3.44||17.92||19.04||21.22||23.23||25.44||27.32||28.06||29.49|
|45–54||23.43 ± 3.47||17.87||19.03||21.09||23.42||25.65||27.34||28.13||29.44|
|55–64||23.15 ± 3.73||16.84||18.02||20.72||23.31||25.40||27.02||28.22||29.90|
|≥ 65||22.36 ± 3.80||16.17||17.63||19.59||22.22||24.80||26.29||27.34||29.37|
|All men||22.70 ± 3.54||17.30||18.37||20.27||22.49||24.90||26.56||27.52||29.30|
|BMI (kg/m2)*,†||19–34||22.36 ± 3.82||16.63||17.59||19.63||22.21||24.89||26.48||27.55||29.34|
|35–44||23.97 ± 4.17||17.06||18.59||21.08||23.74||26.83||28.89||29.90||31.25|
|45–54||24.07 ± 4.18||16.97||18.30||21.12||23.74||27.27||28.97||30.01||31.19|
|55–64||23.90 ± 4.30||16.88||18.17||21.11||23.47||26.73||28.91||30.08||31.25|
|≥ 65||22.52 ± 4.12||15.76||17.05||19.37||22.51||25.30||26.99||28.31||29.59|
|All women||23.04 ± 4.09||16.65||17.78||20.03||22.79||25.78||27.56||28.90||30.45|
*Significant mean difference between age ranges in both men and women (
BMI, body mass index; SD, standard deviation.
Estimated crude ORs demonstrating the risk of overweight and obesity (BMI ≥ 25.0 kg/m2) and obesity alone (BMI ≥ 30.0 kg/m2) in Pakistani adults
|Characteristics||Crude OR (95% CI)|
|BMI ≥ 25.0 kg/m2||BMI ≥ 30.0 kg/m2|
|35–44||1.98 (1.77–2.23)||2.34 (1.86–2.95)|
|45–54||1.99 (1.75–2.26)||2.28 (1.77–2.94)|
|55–64||1.86 (1.60–2.16)||2.49 (1.87–3.31)|
|≥ 65||1.18 (0.99–1.40)||1.18 (0.80–1.75)|
|Women||1.34 (1.23–1.47)||2.01 (1.64–2.47)|
|Ever-married*||1.92 (1.70–2.16)||2.35 (1.76–3.14)|
|Area of residence|
|Urban||1.23 (1.12–1.35)||1.28 (1.06–1.55)|
*Includes married/living with partner and divorced/separated/widower.
OR, odds ratio; BMI, body mass index; CI, confidence interval.
Estimated crude ORs demonstrating the risk of overweight including obesity (BMI ≥ 25.0 kg/m2) and obesity alone (BMI ≥ 30.0 kg/m2), stratified by rural and urban residence
|Characteristics||Crude OR (95% CI) of rural adult||Crude OR (95% CI) of urban adult|
|BMI ≥ 25.0 kg/m2||BMI ≥ 30.0 kg/m2||BMI ≥ 25.0 kg/m2||BMI ≥ 30.0 kg/m2|
|35–44||1.93 (1.68–2.21)||2.47 (1.86–3.28)||2.08 (1.69–2.57)||2.04 (1.37–3.06)|
|45–54||2.00 (1.72–2.34)||2.43 (1.78–3.31)||1.92 (1.52–2.42)||1.97 (1.27–3.06)|
|55–64||1.69 (1.42–2.02)||2.69 (1.92–3.77)||2.42 (1.81–3.23)||2.13 (1.25–3.61)|
|≥ 65||1.29 (1.06–1.58)||1.36 (0.88–2.13)||0.85 (0.58–1.25)||0.80 (0.34–1.90)|
|Women||1.33 (1.20–1.49)||1.80 (1.41–2.29)||1.35 (1.14–1.60)||2.62 (1.77–3.89)|
|Ever-married*||1.70 (1.47–1.96)||2.06 (1.47–2.90)||2.63 (2.10–3.29)||3.24 (1.89–5.55)|
*Includes married/living with partner and divorced/separated/widower.
OR, odds ratio; BMI, body mass index; CI, confidence interval.
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