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ORIGINAL ARTICLE
Year : 2016  |  Volume : 19  |  Issue : 3  |  Page : 125-130

Comparison of health-care expenditure of obese and non-obese patients attending a tertiary health-care institution in Northwest, Nigeria


1 Department of Psychiatry, Bayero University Kano, Kano, Nigeria
2 Department of Community Medicine, Bayero University Kano, Kano, Nigeria
3 Department of Community Medicine, Aminu Kano Teaching Hospital, Kano, Nigeria

Date of Web Publication14-Oct-2016

Correspondence Address:
Musa Usman Umar
Department of Psychiatry, Bayero University Kano, Kano
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1118-8561.192391

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  Abstract 

Background: The World Health Organization estimates that obesity is responsible for between 2% and 7% of global health-care spending. Obesity has a huge public health significance considering that about a third of the global population is either overweight or obese, and Nigerian's obesity burden is also increasing. The aim of the study is to compare the pattern of health-care expenditure between obese and nonobese. Materials and Methods: This was a comparative study of patients attending the general outpatient department of Aminu Kano Teaching Hospital, Kano, Nigeria. A questionnaire to assess the pattern of health-care expenditure based on the Andersen Behavioral Model was adopted for this study. Results: Of the 325 participants, 117 (36%) were obese, while 208 (64%) were nonobese. Obese individuals had statistically significant higher median cost of total inpatient cost at ₦88000 compared to ₦45000 (P = 0.015). The total outpatient cost was statistically higher for obese compared to nonobese (P < 0.001), so also was the cost of physician consultation (P < 0.001), laboratory and radiological tests (P < 0.001), cost of medication (P < 0.001), and alternative health-care services (P = 0.003). For indirect cost, the difference in mean number of days given excused duty from work and unable to carry out household activities were statistically higher for obese than nonobese (t-test = 3.068; P = 0.002) and (t = test = 5.995; P < 0.001), respectively. Conclusion: In this study, the cost differential of obesity compared to nonobese individuals was substantial, and this is likely to place a lot of economic burden to the individual and the health-care system.

Keywords: Health-care expenditure, indirect cost, inpatient cost, obesity, outpatient cost


How to cite this article:
Umar MU, Sanusi A, Garba MR. Comparison of health-care expenditure of obese and non-obese patients attending a tertiary health-care institution in Northwest, Nigeria. Sahel Med J 2016;19:125-30

How to cite this URL:
Umar MU, Sanusi A, Garba MR. Comparison of health-care expenditure of obese and non-obese patients attending a tertiary health-care institution in Northwest, Nigeria. Sahel Med J [serial online] 2016 [cited 2023 Sep 24];19:125-30. Available from: https://www.smjonline.org/text.asp?2016/19/3/125/192391




  Introduction Top


Obesity is linked to increased health-care cost.[1],[2],[3] There is a positive association between excess weight and health-care expenditure.[1],[4],[5] Withrow and Alter reviewed studies on the direct costs of obesity worldwide and reported that obese individuals with body mass index (BMI) greater than 30 kg/m 2 have around 30% higher medical costs than those without obesity.[5]

In most developed countries, obesity ranks among the top three human-generated economic burdens.[1],[6],[7] The 2014 report of the McKinsey Global Institute reported that the global impact of obesity is about 2 trillion United States Dollar, or equivalent to 2.8% of global gross domestic product, affecting both developed and developing countries.[6] Obesity has the same impact on the global economy as armed conflict and only slightly less than smoking.[6] Globally, it is the third leading cause of social burden generated by human beings and 13th in Nigeria.[6] The productivity lost from the effect of obesity using disability-adjusted life years is around 71% from premature death and 29% to disability, with the latter affecting employers through lost employee productivity and health-care cost.[1],[2],[4] Obesity is also associated with absenteeism from work, depression, and frequent utilization of health-care services.[6],[7],[8] This is of huge public health significance in view of the fact that about 30% or 2.1 billion of the global population is said to be overweight or obese.[9] The prevalence of obesity in Nigeria range from 8.1% to 22.2%.[10]

Obesity is associated with poorer health status, increased utilization of health services, and increase in direct cost.[2],[11],[12] It is also associated with significant indirect costs or burden to the individual, family, and society from absenteeism from work, increased comorbidities, disability, and premature mortality.[2],[13] Evaluating the health-care uses and costs accrued by individuals with obesity are essential in formulating cost-effective obesity intervention programs.[14] The usual assessment of disease burden by deaths or years lived with a disability is a useful indicator as it may inform various methods for prevention of a condition by accounting for health loss but usually, it does not generally reflect the needs or utilization of health-care services.[15] Therefore, an alternative approach is to quantify the impact of the known condition's risk factors, in this case, obesity on health-care expenditure.

In Nigeria, both electronic and manual searches yielded no studies on the health-care expenditure of obese individuals. It is therefore imperative for a study in this line to assess the pattern of health-care expenditure among obese individuals in Nigeria toward understanding the burden of obesity on the health-care system. The objectives of the study included the assessment of health-care costs in terms of inpatient and outpatient care, diagnostic services, medication, alternative care, and indirect cost.


  Materials and Methods Top


Setting

This study was conducted at the general outpatient department (GOPD) of Aminu Kano Teaching Hospital (AKTH) Kano State, Nigeria. It is a 500-bed tertiary teaching hospital located within Kano metropolis and was established to primarily serve the needs of Kano State and other neighboring states in the country.

The GOPD is a part of the Department of Family Medicine located within the hospital. Approximately, 340 new patients and 1320 follow-up cases of adult patients are seen at the GOPD every week, and it is the first point of contact for nonemergency cases in the hospital. It has 4 consultants, nearly 33 residents and medical officers, and ten nurses.

Study population

The study population consisted of all individuals attending the GOPD of AKTH during the period of study (both obese and nonobese). The inclusion criteria for selecting respondents were patients aged 16 years and above, must have been registered with the hospital for at least 12 months prior to the study, must have had a consultation that was recorded in their case files for at least two visits, and they must have given informed consent.

Study design

A comparative study was used. An estimated sample size of 325 patients using the prevalence rate of 12% from a study conducted in Sokoto state.[16] Purposive sampling technique was used to select AKTH, Kano, using patients on follow-up attending the general outpatient clinic who met inclusion criteria for the study. On each day, for a period of 12 weeks, all the patients on follow-up were triaged based on their BMI into normal weight, overweight, and obese. On each day, after a patient with obesity was selected the next consecutive patients with overweight and then normal weight were selected. Patients that were obese, overweight, and normal weight were recruited until the estimated sample size was obtained. Patients that were obese were those that had BMI of ≥30 kg/m 2, while none obese consisted of patients that had BMI of <30 kg/m 2 (both those with normal weight and overweight).

Instruments and methods of data collection

Sociodemographic and health-care utilization questionnaire

The sociodemographic questionnaire was designed to assess the sociodemographic data of patients. The demographic characteristics include age, sex, religion, marital status, socioeconomic status, and highest educational level. The health-care utilization part of the questionnaire consists of the determinants and need factors of health resource utilization in the context of Andersen Behavioral Model.[17] All the assessment of the content of this questionnaire was through the interview. Health-care utilization questionnaire is an adopted tool based on the Andersen Behavioral Model. Inpatient costs that were assessed included hospitalization, cost of medication, and cost of investigation for the last 12 months. While the outpatient costs included the cost of physician consultation, laboratory tests, radiological tests, medication, and alternative medicine or complementary medicine for the past 12 months. All cost were in Naira, the country's currency. Indirect cost was assessed through the number of days excused duty was given for employed individuals and the number of days unable to work unemployed patients. The cost for alternative or complementary care received over 12 months which consisted of herbal medicine and Islamic medicine and/or rukiya (exorcism) were included.

Assessment of obesity

The Body Mass Index (BMI, i.e., kg/m 2) was calculated as weight (in kg) divided by a square of the height (in meters), and it is categorized using the World Health Organization definitions, i.e., BMI of 18.5–24.9 kg/m 2 is the reference (“normal” BMI), 25–29.9 kg/m 2 is defined as overweight while ≥30 kg/m 2 as obesity. Anthropometric measurements were first done by taking weight to the nearest 0.1 kg using a weighing scale, while a stadiometer was used for the measurement of height. A SECA weighing machine (seca 700) with an inbuilt stadiometer was used in the study, it had a maximum weight capacity of 220 kg, minimum capacity of 2 kg, and precision error of 0.1 kg, while the measuring rod or stadiometer range from 24 to 78 inch (http://www.seca.com/en_us.html).

Ethical consideration

Ethical clearance and approval for conducting the study were obtained from the Research Ethics Committee, AKTH Kano (NHREC/21/08/2008/AKTH/EC/14010), together with the permission of the Head, Department of Family Medicine, AKTH, Kano, Nigeria. Informed consent was also obtained from all patients prior to the interview. There was no envisaged risk to study participants, and obese patients were counseled or referred as appropriate in conjunction with the relevant consulting physician.

Data management and analysis

Data were entered into Excel Spread Sheets and cleaned. Data analysis was done using the Statistical Package for Social Sciences (SPSS) Version 16 (Released 2007. SPSS for Windows, Version 16.0. Chicago, USA, SPSS Inc). The result was presented using charts and tables. Quantitative variables were reported using means and standard deviation. The various costs incurred by obese and nonobese patients were assessed and presented using descriptive statistical tools, such as medians and frequency tables as appropriate. The relationship between sociodemographic and other health variables with obesity was assessed using Chi-square. The differences between obese and nonobese individuals in terms of their health-care expenditure was tested using the Mann–Whitney U-test as expenditure is generally not equally distributed. For the indirect cost, the Student's t-test was used. A value of P < 0.05 was used as the level of significance for statistical tests.


  Results Top


Sociodemographic variables

Of the 325 participants studied, 117 (36%) were obese, while 208 (64%) were not obese. The mean age of the obese patients was 42.3 ± 10.0 years, while the mean age of the nonobese respondents was 39 ± 12.3 years.

[Table 1] presents the comparisons of the sociodemographic variables between the obese and nonobese patients and showed that the obese and nonobese respondents were significantly different in gender composition, marital statuses, insurance statuses, and the presence of other comorbidities.
Table 1: Sociodemographic variables of the respondents

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Inpatient expenditure

For the study participants that were obese, the median cost (in Naira, ₦) of hospitalization was higher (₦48000) higher than the nonobese (₦25000). This difference was not statistically significant (P = 0.063). The median cost of medication during hospitalization in the last 12 months was higher for obese individuals compared to nonobese: ₦23000 versus ₦15000. The difference was not statistically significant (P = 0.055). Obese individuals had higher median cost of investigations (₦27000) compared to nonobese (₦7360) patients [Table 2]. This difference was statistically significant (P = 0.006).
Table 2: Pattern of health-care expenditure among obese and nonobese participants

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The median inpatient cost was ₦88000 for obese participants and more than ₦45000 for nonobese group [Table 2]. The difference in the median cost of inpatient care was statistically significant (P = 0.015).

Outpatient expenditure

The median cost of physician consultation over a 12-month period for obese patients was ₦1600, higher than that of nonobese individuals (₦1000) for nonobese individuals [Table 2]. The difference was statistically significant (P < 0.001). For laboratory tests [Table 2], the median cost was higher for obese compared to nonobese participants: ₦3855 versus ₦2000. This difference was statistically significant (P < 0.001). The median cost of radiological services was also higher for obese as ₦4500 compared to ₦2000 for nonobese individuals [Table 2]. The difference in the cost of radiological services in the last 12 months was statistically significant (P < 0.001).

The median cost of medication (₦39550) was higher for obese compared with nonobese (₦15900) [Table 2]. The difference was statistically significant (P < 0.001).

For the use of alternative or complementary health services, the population that was obese reported the higher median cost of services (₦26500) in the past 12 months compared to nonobese (₦9000). The difference was statistically significant (P = 0.003).

The median outpatient cost was much higher for obese patients at ₦57000 compared to the nonobese (₦22450). This difference was statistically significant (P < 0.001).

Total cost of medical care

The median cost medical care in the last 12 months for obese individuals (₦57130) was higher for nonobese (₦22500). This difference was statistically significant (t-test = 6.047; P < 0.001) [Table 2].

Indirect cost

The mean number of days individuals, who were employed, that were obese and given excused duty in the past 12 months was higher than those that are nonobese: 4.98 ± 5.01 days versus 2.81 ± 4.29 days [Table 3], and the difference was statistically significant (t = 3.068; P = 0.002). Unemployed individuals that were obese had a higher mean number of days unable to carry out household chores (17.67 ± 19.41 days) compared to nonobese (3.13 ± 9.83 days). This difference was statistically significant (t = 5.995; P < 0.001).
Table 3: Pattern of indirect cost among obese and nonobese

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For the number of times excused duty was given in the last 12 months, those that were obese had a mean of 1.39 ± 1.41 times which was higher than the mean of those that were nonobese 0.83 ± 1.15 times. The difference was statistically significant (t = 2.889; P = 0.004).


  Discussion Top


The total inpatient cost in this study was higher for obese individuals than for nonobese. This is in keeping with other studies that shows a positive association between excess weight gain and health-care expenditure.[1],[4],[15],[18] Withrow and Alter reviewed studies on the direct costs of obesity worldwide and reported that obese individuals with BMI greater than 30 kg/m 2 have around 30% higher medical costs than those without obesity.[5] Another review of direct medical costs of overweight and obesity in the USA reported that the incremental per capita cost for overweight was 9.9% greater, and for those with obesity, it was 42.7% greater than the cost for individuals with normal weight.[18] In this study, there was no association between obesity and cost of hospitalization. A study by Migliore et al. of patients admitted into medical ward and obesity rehabilitation unit of a specialized obesity center in Italy, the severity of obesity did not affect the costs of hospitalization.[8] The study cohort was that of obese patients without comparison with the reference BMI or normal weight (20–25 kg/m 2) unlike in other studies.[19],[20] Our study also combined both individuals with normal weight and overweight as a comparison group, and the effect of overweight individuals may reduce the effect of the association.[18] It has been suggested that the relationship between overweight and costs was slightly j-shaped in a number of studies, i.e. overweight was not associated with higher costs, when compared with normal weight,[4],[21] the majority of the studies found increasing costs over the whole excess weight range.[22],[23] In this study, the cost of obesity was mainly derived from investigations and less from prescription drugs, unlike other studies where the impact of the cost of obesity is derived mainly from prescription drugs.[7]

For the outpatient services, variables such as costs of physician consultation, investigations, prescription drugs, alternative or complimentary services, and the total outpatient cost were higher in obese compared to nonobese. Like in this study, others have reported excess cost in obese individuals. The increased health-care expenditure was derived from consultations with general practitioners, specialist care, prescribed prescription, and investigations.[6],[19],[22] Though other studies did not find any association between obesity and health-care expenditure.[24]

The indirect cost of obesity also contributes to the overall higher expenditure through a decrease in workforce productivity.[25],[26] Absenteeism refers to the time absent from work as a result of illness and is usually measured as sick leave or sickness absence.[25] Obese individuals in this study reported more sick leave days and more number of times sick leave were requested in 12 months. Studies using both cross-sectional and longitudinal methods report that obese employees took more sick leave and had higher sick leave attributable cost than individuals with normal weight.[26],[27] In a retrospective study in the USA with 11,728 health-care and university employees, the lost workdays ranged from 3.39 for those with BMI 30–34.9 kg/m 2 to 8.04 for BMI ≥40 kg/m 2.[28]

In this study, the difference seen in the increased health-care expenditure for obese compared with nonobese patients was likely to be associated with the patients' health beliefs and help-seeking behavior. Obese patients generally believe that they have increased risk for health problems and thereby making more frequent hospital visits to their physicians to prevent the perceived problem. In addition, physicians may request for more follow-up visits and diagnostic tests with the aim of preventing known risk factors of obesity. Thus, this differential care and diagnostic testing may be happening in the absence of health status differences because it is motivated by perceived risk for potential health problems.[29] This eventually will increase the health-care expenditure.


  Conclusion Top


In this study, the cost differential of obesity compared to nonobese individuals was substantial, and this is likely to place a lot of economic burden to the individual and the health-care system. It is recommended that prompt and effective management for obesity should be instituted by policy makers as it may reduce the financial burden associated with the condition. This may serve as a template for formulating cost-effective obesity intervention programs.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Tables

  [Table 1], [Table 2], [Table 3]


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