Anthropometric measurements and prevalence of underweight, overweight and obesity in adult Malawians: nationwide population based NCD STEPS survey

Introduction Overweight and obesity are significant causes of increased morbidity and premature mortality from non-communicable diseases, particularly in sub-Saharan Africa, although local high quality population-based data to inform policies and strategies are lacking. Methods Using the WHO STEPwise approach to chronic disease risk factor surveillance, population-based nationwide survey was conducted on participants aged 25-64 years in Malawi. A multi-stage cluster sample design and weighting were used to produce a national representative data for that age range. Results A total of 4845 participants (65.7% females, 87.6% from rural areas) had complete anthropometric data and included in this analysis. Overall (both sexes) population-based mean body weight, height, systolic blood pressure, diastolic blood pressure, blood glucose and cholesterol were estimated at 58.7 kg, 159.9 cm, 133.4 mmHg, 79.5 mmHg, 4.3 mmol/L, 4.4 mmol/L respectively. Prevalence of underweight, overweight, obesity, overweight and/ or obesity and central adiposity were 6.5%, 17.3%, 4.6%, 21.9% and 28.8% respectively. Overweight, obesity, overweight and/ or obesity and central adiposity were more frequent in females than males (20.7% vs 14.1%, 7.4% vs 2.0%, 28.1% vs 16.1% and 52.8% vs 5.6%), in urban than rural areas (23.2% vs 16.6%, 12.0% vs 3.7%, 35.2% vs 20.2%) respectively. Conclusion This study demonstrated that overweight and/ or obesity is the major public health problem affecting at least one in five adults in Malawi. The problem is more frequent in females than males and urban than rural. Implementation of primary health care approaches such as WHO package for essential non-communicable diseases could reduce the problem.


Introduction
Overweight and obesity are the major risk factors for increased morbidity, disability, and premature mortality from cardiovascular disease (mainly hypertension, heart disease and stroke), type 2 diabetes mellitus; musculoskeletal disorders (osteoarthritis and chronic back pain) and some cancers (endometrial, breast, and colon) [1][2][3][4]. It is estimated that the burden of hypertension attributable to obesity is approximately 80% for men and 60% for women; the odds ratio for hypertension is 1.7 for overweight compared with normal weight individuals. Using body mass index (BMI) as an anthropometric measure of adiposity, each 5 units above the overweight category (BMI ≥ 25 kg/m 2 ) is associated with approximately 30% higher overall mortality and 40% higher for cardiovascular mortality [5][6][7]. Once considered as a health problem for high-income countries, overweight and obesity are now on the rise in low-and middle-income countries, particularly in urban settings. In sub-Saharan Africa (SSA), the global epidemic of overweight and obesity -"globesity" -is rapidly becoming a major public health problem because of uncontrolled rapid urbanisation and changes in lifestyles. It is estimated that 25% to 60% of urban women are overweight, prevalence of hypertension (defined as blood pressure of 140/90 mmHg or more) is on the rise and commonly exceeds 20%-25% in rural areas, 30% in urban and semi-urban areas and prevalence of diabetes of up 16% (range 0% to 16%) have been reported. Type 2 diabetes accounts for over 90% of diabetes in sub-Saharan Africa [8][9][10][11][12][13].
In Malawi, just like other sub-Saharan countries, recent populationbased data suggest that non-communicable diseases and their risk factors are major public health problems with estimates of age-sexstandardised cancer incidence rate per 100, 000 population increasing from 31 to 56, 29 to 69 in males and females respectively in the period 1999-2002 to 2007-2010 [14]. Between July and  [15][16]. In this paper, the detailed findings on the anthropometric measurements and prevalences of underweight, overweight and obesity and their correlates are presented.

Study design and sample size
This study was a nationwide population-household-based crosssectional survey designed according to a WHO STEPwise approach to chronic disease risk factor surveillance [17]. Sample size, calculated using the standard formula, was adjusted for design effect for complex sample design set at 1.5, age-sex estimates in the 25-64 age range (8, 10-year intervals) and a non-response rate of 20%. With these adjustments, the final required sample size was 5,760. It was assumed that the non-response rate would be high because participants may refuse blood testing and/ or adhere to fasting, the latter being required for fasting blood glucose testing.

Sampling of survey sites, households and eligible participants
Enumeration areas (EAs) were used as survey sites.
Administratively, Malawi is divided into twenty-eight districts. In turn, each district is subdivided into smaller administrative units called traditional authorities (TAs). Each TA is sub-divided into EAs by the National Statistical Office (NSO). Enumeration areas are classified as urban or rural. Each EA has demographic data and a sketch map. The sketch map shows the EA boundaries, location of buildings, and other landmarks. The list of all EAs in Malawi from population and housing census conducted in June 2008 was obtained from NSO. This list was used as a sampling frame for the random selection of EAs. According to the WHO NCD STEPS Survey manual Part 2 section 2 [17], in each EA 30-50 households could be selected and in each household only one eligible participant could be selected. We settled for 40 households per EA. Therefore to reach the required sample size, the total number of EAs to be selected was 144 EAs (5760/40). The 144 EAs were randomly selected nationwide using the probability proportional to size (PPS) sampling method. In each EA, 40 households were randomly selected using systematic sampling method. Sampling interval was calculated by dividing the total number of households in the EA as given by the NSO by 40 (the number of households to be selected).
At household level, only one eligible participant was selected using the Kish sampling method built-in personal digital assistant (PDA, HP iPAQ). Households with no eligible participant were not replaced.

Recruitment of participants and data collection
Eligible participants were all adults aged 25-64 years. Participants were involved in the study for two days: day one was for the questionnaire and anthropometric measurements and day two was for blood pressure measurement and laboratory tests. Formal written consent was obtained. Participants with abnormal physical or laboratory findings as defined below were counseled and referred to their nearest health facility for further action and follow up. Body measurements and laboratory tests were performed by nurses and clinical officers while enumerators conducted the interviews. A total of seven survey teams, each with 8 members were deployed to collect data over a period of 30 days between July and September 2009.

Step 1: demographic and lifestyle data collection
Demographic and lifestyle data were collected using WHO STEPS questionnaire. The questionnaire was programmed on PDA. It

Step 2: Anthropometric measurements
Anthropometric measurements that were performed were; body weight, height, waist and hip circumference and blood pressure.
Body weight measurements were taken on a pre-calibrated weighing bathroom scale (Seca gmbh & Co., Hamburg, German).
The scales were calibrated daily using a known weight (1kg packet of sugar). Participants were weighed dressed in light clothing and barefoot. Measurements were taken to the nearest 0.1 kg. Height was measured with the participant standing upright against a wall on which a height mark was made. Measurements were taken with the participant in barefoot, standing with the back against the wall and head in the Frankfort position with heels together. The participant was asked to stretch to the fullest. After being appropriately positioned, the participant was asked to exhale and a mark with a white chalk was made to mark the height. The height was then measured in centimeters from the mark to the floor using the tape-measure. Measurements were taken to the nearest 0.1 cm.
Waist circumference was measured using a tape-measure in centimeters, and the measurement was made in the mid-axillary line midway between the last rib and the superior iliac crest.
Measurements were taken to the nearest 0.1 cm. Hip measurement was also made using a tape-measure placed horizontally at the point of maximum circumference over the buttocks. Measurements were taken to the nearest 0.1 cm. Blood pressure measurements were taken using battery powered digital blood pressure machines (Omron® M4-I, Omron Healthcare Co. Ltd, Hoofddorp, The Netherlands). The participant was asked to sit on the chair and rest quietly for 15 minutes with his/her legs uncrossed. The left arm of the participant was then placed on the table with the palm facing upward.Three readings, 3-5 minutes apart, were then taken on the left arm. During the analysis the average of the last two readings was the final blood pressure reading.

Step 3: Biochemistry laboratory measurements
On the first day of the survey after step 1 and step 2, participants were asked to starve overnight. Consenting participants were asked not to consume any food except for water after taking supper/dinner of that day until the survey team came again in morning of the following day (day 2). People converged at the agreed place in their community where finger prick blood samples for biochemistry tests were taken. Those that complied with the advice (starving overnight) were eligible for finger prick blood sample collection. Total cholesterol and fasting blood glucose were measured using Accutrend ® Plus machines (Roche, Mannheim, Germany).

Data management
Data were collected electronically using PDAs programmed with WHO e-STEPS software. There were two sets of PDAs, one set for Step 1 (questionnaire) and Step 2 (anthropometric measurements) and the other set for Step 3 (biochemistry measurements). Diastolic blood pressure ≥ 110 mmHg or systolic ≥ 180 mmHg was considered as severe hypertension. Raised fasting blood glucose was defined as blood glucose level ≥ 7.0 mmol/L or currently on medication for diabetes mellitus (documented in the health booklet).
Raised total cholesterol was defined as cholesterol level ≥ 5.0 mmol/L [17][18]. The detailed methods and materials have also been presented elsewhere [15][16]. Results were considered statistically significant, p<0.05 or t<0.05.

Ethical approval was granted by the Malawi National Health Sciences
Research and Ethics Committee. Written informed consent was obtained before participants were enrolled in the study using the WHO NCD STEPS survey consent form.  Table 2).

Factors associated with overweight and/ or obesity (BMI ≥ 25 kg/m 2 )
In uni-variate analysis, female gender, urban dwelling, not smoking tobacco, high blood pressure, high fasting blood glucose and high blood cholesterol were significantly associated with overweight and/ or obesity. Overweight and/ or obesity were more frequent in those with low than those with moderate or high levels of physical (24.6% vs 21.7%) but the association was not statistically significant (table   3). In multi-variate analysis (logistic regression), female gender, urban dwelling, age 35-44 years old, currently married or cohabiting, not smoking tobacco, high blood pressure and high blood cholesterol were important factors/conditions associated with overweight and/ or obesity ( Table 3). under nutrition not overweight was major public health problem in adults then [19][20][21]. In adults, overweight/obesity increases with increasing age and therefore it is unlikely that differences in age group of study participants    [24][25][26][27][28][29].

Discussion
Our findings of female gender, urban residence and age as significant risk factors for overweight/obesity and that overweight/obesity is associated with hypertension were consistent with findings from other studies [23][24][25][26][27][28][29]. However, this study is one of the few studies (if any) in sub-Saharan Africa to document the association between BMI and tobacco and alcohol use.
Overweight/obesity was more frequent in non-tobacco smokers than smokers (24.0% vs 10.2%), non-alcohol drinkers than drinkers (22.9% vs 17.3%) consistent with findings from other studies that tobacco use is associated with low BMI [30]. All forms of tobacco produce free radicals that deplete antioxidants like Vitamin C, E and carotenoids and cause oxidative damage to DNA, proteins and lipids. Tobacco use also impairs the immune system, making tobacco users more susceptible to infectious agents. The interactions between oxidative stress and infections caused by tobacco use could explain why tobacco use is associated with low BMI [30]. In this population, level of education attained, physical activity, blood cholesterol and fasting blood glucose were associated with overweight/obesity but the associations were not statistically significant.
Observations from this study that adult Malawian males were taller, heavier and had higher systolic blood pressure than females, that females had higher body mass index, hip circumference and heart rate than males, and that adults in urban areas were heavier, had higher body mass index and hip circumference than in rural areas were also consistent with findings from previous population-based studies in Malawi and SSA region [19][20][21][24][25][26][27][28][29] In SSA, large body shape (overweight/obesity) is perceived as being rich in males, sexually attractive in females and healthy-interpreting fatness as a sign of good health and absence of disease [33][34].
This misconception emphasises the need of taking into account gender and socio-cultural issues when developing and implementing evidence-informed lifestyle health promotion interventions. Change is more likely to happen if/when the concerned individual understands that there is a problem that needs changing [35].

Limitations of the study
Over-representation of females was one of the limitations of this study; two thirds of participants were females. However, it was unlikely that this had an influence on the results for women because data were weighted (standardised) for age and sex to national

Conclusion
This study demonstrated that overweight and obesity were the major public health problems in Malawi affecting one in five adults (overall), one in three women and one in three people in urban areas. Risk factors and the need for taking into account gender and socio-cultural issues when developing and implementing evidenceinformed strategies and interventions for lifestyle health promotion have been highlighted. Implementation of WHO package for essential non-communicable diseases could prevent and control overweight.
This study was co-funded by Malawi Ministry of Health and World Health Organisation. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of this manuscript.