BENCHMARKING FIJI’S HEALTH STATUS: PACIFIC AND GLOBAL COMPARISON

 Author: Dr. Sheetal  Preet Singh

BACKGROUND
Benchmarking    refers    to    “the    process    of systematically searching for and incorporating international best practice into an organization”. In the context of a country striving for better health outcomes, it can be described as a quality improvement technique to compare with other countries with the aim of reviewing the process that  has  proven  effective. Benchmarking, however,   may   be   difficult   due   to   various challenges.   These include selection of relevant countries    for comparison,    agreement    on particular  standards,  availability  of  data  for similar    time    periods    among    comparator countries  and  variations  in  interpretation  of
parameters being compared.

OBJECTIVE
The purpose of this article is to compare Fiji’s health status with other countries in the Western Pacific region and globally.

METHODOLOGY
Data  used  for  comparison  was  mainly  from Country  Health Information  Profiles (CHIPs). However for more recent data for some of the indicators reference was made to the Draft 2011 Annual Report4.  Reference was also made to the most recent publication on achieving the health- related  MDGs in  the  Western  Pacific Region (2012). Further, the International Comparisons Report6  was used for making comparisons against other countries beyond the Western Pacific region.

This article provides an analysis on Demographics, socio-economic status and  health status.   The health  status  indicators  comprise  of measures for Non Communicable Diseases (NCDs), Communicable  Diseases (CDs), maternal  and child health  and  human  resources for health. Average values for the various comparator countries were calculated.  The countries in the Pacific which are  compared  with  Fiji include Cook  Islands,  Federated  States of Micronesia (FSM), Kiribati, Marshall Islands, Nauru, Palau, Papua  New Guinea  (PNG),  Samoa, Solomon Islands, Tonga, Tuvalu and Vanuatu.  Among the G7 countries compared with Fiji in this article include: United States, Germany, France, Canada, Australia,  Italy, New  Zealand,  Sweden, Japan and United Kingdom (UK).  However, for some of the indicators where data was not available from particular countries, those countries were excluded from the analysis.

RESULTS AND DISCUSSION
1. Life Expectancy

The life expectancy at birth in Fiji is 69, with females living on average 4 years more than males7. The difference in male and female life expectancy is similar to the average of the countries being compared, including the UK.   However, some countries such as Kiribati and Palau have larger differences between the sexes such as 5-7 years. More developed countries such as Australia and New Zealand reported  life expectancy at birth of 82 and 81 years respectively.  Cook Islands, Samoa and Vanuatu also reported slightly higher life expectancy than Fiji.

2. Socio-economic Indicators

According  to  the  National  Health  Accounts, 2009-2010, the total healthcare expenditure  in Fiji as a proportion of GDP has varied from 4.2 to 4.9% over the past 4 years and the major source of funding has been from the Government budget. The average of 4.6% over the 4 year period is just under the 5% average proportion recommended by the  Health  Financing  Strategy of the  Asia Pacific Region (2010-2015) in order for countries to  progress in  attaining  universal coverage of basic  health  care  services8. Other  significant sources of funding for Fiji include private sector and development partners. Over the years, donor funding has increased from FJ$6.9m (2007) to FJ$22.1m (2010). NGO contributions have also increased from FJ$3.7m (in 2009) to FJ$7.5m (in 2010).8 However, health expenditure in Fiji, as a percentage of GDP, is merely half in comparison to most of the G7 countries having an average of about 8.9%.

On average, the total Government Health Expenditure as a percentage of GDP has been stable at about  3.1% over the past 8 years, in contrast to the rising health expenditure trends noted in other countries.   The National Health Accounts also reveal that the total Government Health Expenditure has been relatively constant at about 7-8% of Total Government Expenditure. Hence, this is about 2-4% less than the WHO recommended benchmark of 8% -10% for Governments to spend on health in order to ensure equal access to health care.

The Human Development Index, which is a measure of the average achievements in a country considering  variables such  as  life expectancy, educational attainment and real GDP per capita, is 0.61 for Fiji. This is less than Australia (0.94), New  Zealand   (0.91),  Samoa   (0.77),  Tonga (0.68) and Vanuatu 0.69).  Considering that Fiji has a high adult literacy rate of 94%, areas for improvement  may include life expectancy and real GDP per capita.

3. Health Indicators

Non Communicable Diseases
Assuming that the figures presented in the WHO CHIPS 2011 for individual countries are incident cases of Diabetes, Fiji reported an incidence of about 1 per 1000 population.   However, this is very much under reported  through the Diabetes Notification forms; hence the incidence is likely to be much higher. FSM and Tuvalu reported the highest rates.

The admission rate for hypertension  in Fiji is about  102 per 1000 population.   FSM, Nauru and Tuvalu have more than 2,000 admissions per 1000 population.
The highest incidence rates for cancer were reported by Australia (485 per 100,000) and New Zealand (451 per 100,000). Marshall Islands and Palau also had higher incidence rates than Fiji (127 per 100,000). Since the expansion of data sources for cancer to include death certificates and data from  the  Patient  Information  System (PATIS) in 2010, there has been about 2 fold increase in the number of cases reported in Fiji. Among the more developed countries such as Australia and New Zealand, cancer of the breast, colon and rectum were the most common types of cancer reported.   In the less developed countries such as FSM, Marshalls and Nauru,  cervical cancer was the commonest type of cancer.  Likewise in Fiji, cervical cancer is the leading cause of cancer among females followed by breast cancer. Whilst the death rates from cancer in Fiji is about 2-3 times lower than the comparator countries, there is an increasing trend over the past 10 years from about  40 to about  80 per 100,000 population. Death rates from cervical cancer has been increasing in Fiji over the past 10 years from about 7-15 per 100,000 in the early 2000 years to as high as 22 per 100,000 in 2011. Compared to the G7 countries, Fiji has the highest death rates from cervical cancer.

FSM and Palau had the highest rates of circulatory disease,  followed by  New  Zealand.    Among deaths  from  main  circulatory  diseases in  Fiji there is a change in the trend from higher death rates  for  cerebrovascular disease in  the  early
2000 years to higher death rates for ischaemic heart disease and myocardial infarction in recent years.  Nevertheless, the overall death rate from circulatory diseases is about 2 fold lower for Fiji compared to other countries in the Pacific.

Communicable Diseases
The prevalence of TB is about 26 per 100,000 population, which is much lower compared to the other countries in the Pacific. Similarly, the death rate from TB was among the lowest at 3 per 100,000 population.  The highest death rates from  TB were reported  from  PNG, Solomon Islands and FSM.   The proportion  of cases detected and cured under DOTS in Fiji were 91% and 90% respectively. These are comparable with Australia with detection and cure rates of 89% and 80% respectively.

The incidence of Hepatitis A, Hepatitis B and Unspecified Hepatitis  were about  1, 19 and  1 per  100,000 population   respectively for  Fiji. Extremely high rates for Hepatitis B in Nauru and Kiribati were noted.

Fiji’s incidence rates for cholera, dengue and typhoid were most comparable with those reported  by FSM at 0, 12 and 51 per 100,000 respectively. Whilst most countries reported 0 or low numbers of cholera PNG had an incidence of208 per 100,000 population.

The incidence of Gonorrhoea  and  Syphilis in Fiji were 140 and  67 per 100,000 population, which are much lower than the average rates of 452 and 646 per 100,000 for the countries being compared.

Fiji has a very low incidence of Leprosy (0.5 per 100,000 population) and no cases of Malaria and Plague. Leprosy in FSM, Marshalls and Nauru is still high ranging  between 20 and  130 per 100,000 population.   In PNG, Solomon Islands and  Vanuatu,  where Malaria is endemic, high incidence rates ranging between 1,000 and 8,000 per 100,000 population was reported.

The incidence of ARIs and Diarrhoeal Diseases in Fiji was about  6500 and  2900 per 100,000 population respectively, which is most comparable with the figures reported by Nauru.  Kiribati had the highest rates followed by Solomon Islands and Tuvalu.

Fiji is classified as having a low HIV prevalence in adults (0.1%), which is most comparable with NZ.  The highest prevalence rate in the Pacific was reported by FSM, followed by PNG.

It was interesting to note that Fiji had one of the lowest proportions of population using improved drinking water source.  Australia, New Zealand and Tonga had 100% of the population using an improved drinking  water source in both rural and urban areas.  Whilst 87% of the population in urban areas is using an improved sanitation facility in Fiji, the proportion among rural areas is only 55%. This discrepancy between rural and urban areas is also noted in other countries in the Pacific such as FSM, Kiribati, PNG and Vanuatu. Australia, Cook Islands, New Zealand and Samoa are  reporting  high  proportions  of population using improved sanitation facilities in both the rural and urban areas.  WHO advocates strong political leadership and commitment  to further improve  the  coverage of  drinking  water  and sanitation.

Maternal, Child and Infant Diseases
The  Infant  mortality  and  under  5  mortality rates were about 16 and 21 per 1000 live-births respectively for Fiji.  There has been a general decline in infant mortality over the 30 year period, from 33 per 1000 live-births in 1980 to about 13 per 1000 live-births in 2010. Whilst this decline has been about 23% over the last 20 years, another 57% reduction over the next 5 years is required in order for Fiji to achieve its MDG target.   Given the above, WHO’s assessment underscores   the   insufficient  progress   made by Fiji in this area.  Fiji’s statistics were mostly comparable with Tonga and Tuvalu and was less than the average for the Pacific Island countries being compared.  However, the rates were about twice that reported by more developed countries such as Australia and New Zealand. The highest mortality rates were observed by PNG and Kiribati in the Pacific. Among the G7 countries much lower rates were reported ranging between 3 per 1000 live-births in Japan in 2000 to about
15 per 1000 live-births in Italy in 1980.   The International  Comparisons  Report  points  out that increasing the doctors by 10% could result in a 6% decrease in perinatal mortality and a 6.5% reduction in infant mortality6. As outlined in the Report, Fiji also needs to focus on increasing its public financing for health.

In   Fiji  the   percentage  of  low  birth-weight (LBW) was 9% which is similar to the average of the countries being compared in the Pacific region  (10%).   Fiji reported  a 6% prevalence of Underweight  children  less than  5 years of age.  This is less than average of the countries being compared (10%).  PNG had the highest prevalence of 28% followed by Vanuatu at 20%. Kiribati and Nauru had the highest rates of low birth-weight babies, which is 2-3 times higher than Fiji.  WHO recommends improvement in maternal nutrition in order to reduce LBW rate.

The Immunization  Rate for measles has been ranging between 68 and 98% over the past 10 years. It was 83% in 2011 for Fiji. This is similar to the average for the countries being compared. However, coverage surveys have indicated higher rates in Fiji such as 94% (in 2008).  Thus, Fiji’s trends  represented  by  routine  data  compares more closely with those of France, Germany and Italy as opposed to the other countries with much higher rates of >90%. Cook Islands, Nauru and Tonga reported the highest coverage rates among the countries being compared in the Pacific. According to WHO  25 countries have already achieved measles elimination in 2011. Fiji needs to maintain high coverage rates to achieve this goal.

Fiji has a high BCG coverage rate for infants at 96% which is more than the average of 91% among countries being compared.      Likewise Fiji’s coverage rates for DPT3, HepBIII and Pol3 are also very high (>90%), which is in accordance with the average of the Pacific Island countries being  compared.     Cook  Islands,  Nauru  and Tonga reported  the highest rates among these countries.  Among the G7 countries, Fiji’s status is more comparable with Germany, Canada and USA.

The maternal mortality ratio for Fiji is 39.2 per

100,000 live-births.   Much  higher  ratios  were reported by PNG, Nauru and Marshall Islands. It  must   be  recognized  that   every  maternal death has a major impact on the maternal mortality ratio, especially in countries with small population.   PNG reported the highest number of maternal deaths, particularly due to abortion and sepsis. There was one maternal death due to haemorrhage reported by Fiji. However, it should be noted that the categories on maternal deaths in WHO CHIPS did not include all the causes of maternal deaths such as ectopic pregnancy. As a result deaths from other significant causes may be under reported in this report. The low number of maternal deaths can be attributed  to a high proportion of skilled birth attendance (99.6%) in Fiji. Only Samoa, Solomon Islands and Vanuatu among the countries being compared reported less than 90% proportion  of skilled birth attendance.  In addition, the high antenatal care coverage for the first visit in Fiji (100%) could be contributing to safe motherhood, comparable to the more developed countries such as Australia and  New Zealand.   Cook Islands, Tonga  and Vanuatu also report very high coverage rates.

The Adolescent birth rate in Fiji is 15.4 per 1000 girls aged 15-19 years10.   This is about 3 times the number reported by Australia.  The highest rates among the countries being compared in the Pacific were reported  by Marshall Islands (67) and Vanuatu (64).

Anaemia rate was highest in PNG (40%) and Tuvalu (29%) in  the  Pacific.   In  Fiji the  rate was 12%, which is less than the average for the countries being compared.  Some interventions recommended by WHO, which Fiji is implementing to address this problem include: fortification, supplementation, de-worming and improved diets.

In Fiji, 37% of women in reproductive age group used modern  contraceptive methods, which is similar to countries  such as PNG, Tonga and Vanuatu.  Contraceptive use was highest in NZ (72%), FSM (66%) and Australia (65%) among the Pacific Island countries being compared.

Mortality and Morbidity
The leading cause of morbidity in Fiji, as per the draft 2011 Annual Report was diseases of the respiratory system.  This is similar to those found in Solomon Islands and Palau. The second and third leading causes of morbidity in Fiji included certain infectious and parasitic diseases as well as diseases of the circulatory system.  In the more developed countries such as Australia and New Zealand, care involving dialysis and malignant neoplasms respectively were major causes of morbidity.  Tonga, Nauru and Marshall Islands reported pregnancy, childbirth and the puerperium as the leading cause of morbidity.

Diseases of the circulatory system are the leading causes of death in Fiji followed by endocrine/ nutritional    and   metabolic   disorders   (such as diabetes) and neoplasms.   Diseases of the circulatory system was also the leading cause of death in most of the countries being compared such as Australia, Cook islands, FSM, Kiribati, Nauru, Palau, Solomon Islands, Tonga and Vanuatu.

Human Resources for Health
New Zealand had the highest ratio of health workers to population among the Pacific Island countries being compared, followed by Australia, Nauru and Palau.  Nurses comprised the largest proportion of health workers.  In Fiji, for every 100,000 people, there are about 203 nurses, 5 pharmacists, 22 dentists and 40 physicians.  The doctor to population ratio ranged between 1: 2400 and 1: 2700 over the past 10 years in Fiji. When compared to UK, which had the lowest ratio among the G7 countries being compared, Fiji had almost 5 times less doctors per 1000 population.

In 2011 the practicing nurses per 1000 population was approximately 2. Hence, compared to the other countries such as Italy and New Zealand, Fiji has 2-4 times less nurses per population.

LIMITATIONS
Whilst   efforts   were   made   to   allow   valid comparisons between the countries, there were some limitations with the data that could have an effect on the accuracy of the comparisons. These include availability of data for the indicators for all the countries being compared at similar time periods.    Some assumptions had to be made about interpretation of the indicators such as definitional differences and variations in demographic factors.  Also, differences in data sources used could influence comparisons e.g. admission data or incidence data for some of the NCD indicators. Completeness of data may have been an issue due to unavailability of data from the private sector e.g. on human resources and contraceptive prevalence.  There may also have been some variations in data management and reporting of information among the countries e.g. pregnancy, childbirth and puerperium clustered as one group as the leading cause of morbidity in Tonga, Nauru and Marshall Islands. However, it  was not  clear  whether  it  excluded normal pregnancy, childbirth and the puerperium.   In Fiji, data for these admissions are excluded from morbidity reports.

CONCLUSION
This benchmarking exercise shows how  Fiji’s health status  is comparable  with most  of the countries in the Pacific region.  However, when comparing with the more developed G7 countries, there is still major scope for improvement. Challenged by limited financial and human resources, Fiji needs to invest wisely in strategies that have greatest impact to health performance. The critical role of health information is evident for conducting such comparisons between countries for monitoring, implementation efforts and evaluating impact at a higher level. 

Health Information

Journal, Volume 1 Issue 2 - Evidence based Health Practice

AN INTEGRATIVE APPROACH OF KNOWLEDGE TO ACTION WITH POLICY MAKERS IN A SMALL PACIFIC NATION

Author:G.Waqa,Dr.Wendy Snowdon, Dr.Helen Mavoa

ABSTRACT
Objective:  This action-oriented  project  aimed to i) enhance the evidence-informed decision- making skills of policy-makers and advocates in the Pacific nation of Fiji and ii) enhance awareness and utilisation of local and other evidence in the development of policies that potentially improve the  food  and  physical activity environments. The approaches  used  capitalize on  innovative partnerships in translating results of the pacific obesity study to policies that aimed at improving population health. This paper will describe the engagement processes used between health researchers and policy makers in Fiji.

Activities: Selected partners from government and non-governmental  organizations with potential to make or influence policies that improve the eating and physical activity environments.  High level meetings organised with Ministers or Permanent  Secretaries of selected government organisations   and   Chief   Executive  Officers from non-governmental organisations seeking endorsements to the partnerships. Focal points were  delegated  who  nominated   participants that are engaged in policy making. A number of very senior officers who were familiar with the process of policy making from each organisation were  recruited  to  provide  timely  advice and guidance  on  how best to  address  the  obesity research results into policies and how to embed evidence-informed decision making process. Individual participants  selected relevant policy topics and apply evidence-informed decision making processes in formulating policy briefs.

Deliverables: Outcomes of policy briefs

INTRODUCTION
A critical tool in all health  promotion  efforts is policy. It is important  however that  all policy-development for health  is well-justified and reasoned. The recent World Cancer Research Fund report  on policy initiatives stated that “Changes and  developments in public policies and programmes have costs and possible harms as well as benefits. Furthermore, policy-makers have many pressing priorities. Proposals for new policies and actions need to be based on sustained evidence of need and on the best evidence of critical problems and effective solutions. This is especially so when proposals involve substantial expenditure  or  substantial  changes in existing policies and practices. Lists of unexamined policy options are not a sound basis for effective programmes.  Evidence of  effectiveness needs to be produced and scrutinised before a strong and  confident  case can be made.” The use of evidence to inform and guide actions has largely developed from  the  medical field where high quality evidence such as data from randomised controlled trials is commonly available to guide medical practice. Similarly the use of evidence in policy-making is intended to ensure rationality in the process  and to provide policy-makers with a more comprehensive and validated set of options, than would be available without the use of evidence, therefore many recommend it as an integral part of policy-making .

The  effective  transfer   of  research   evidence to policy makers, practitioners and wider populations is therefore an important component of obesity-reduction campaigns. There is however a significant problem with the lack of evidence use in policy-making.
One of the main obstacles to the use of research- based evidence in policy-making is believed to be the presence of a gap between those who produce research and  those  who use it. This hampers communication  and  dissemination  of research findings. For example, how many  health  staff are able to access and regularly read key medical journals?

Canada  has  been  at  the  forefront  of  efforts to  tackle  this  global problem.  The Canadian government  created the  Canadian  Institute  of Health  Research (CIHR), which has a role of championing  knowledge translation  (KT).  Its website is an excellent resource for those wishing to  learn  more   about   knowledge  translation and broking9.   Knowledge translation  is about making users aware of knowledge and facilitating their use to improve health and health care policies  and   systems.  “Knowledge  brokers” are tasked to facilitate the transfer of research and  other  evidence, between  researchers  and decision makers. It  is increasingly recognized that “evidence” in planning and policy decisions must include other  factors like the availability of  resources,  political  context  and  values, to making information  more  available, accessible and attractive to decision-makers capacity to use research. This approach reflects the assumption that barriers to decision-makers’ use of evidence include the availability of data, accessibility and user capacity.

Knowledge-exchange in Fiji
Knowledge Exchange (KE) involves interaction between   decision   makers   and    researchers that  results in a better  understanding  of each other’s work, new partnerships, and the use of research-based evidence in policy and decision- making(8). It is therefore considered a more collaboratively-based approach to knowledge translation  as it recognises the  importance  of two-way communications  between researchers and policy-makers. NCDs are a substantial problem in Fiji, and policy interventions could potentially be important tools to help tackle the issue. Evidence-informed policy development would be of particular benefit, and an innovative project was started  in 2009, entitled  TROPIC (Translational  Research on Obesity Prevention In   Communities)   which  aimed  to   progress and embed the use of evidence-informed policymaking for obesity prevention in Fiji. This is an ambitious approach, particularly given the complexity of the task, to incorporate research evidence in policy and practice decisions. This research is combining practical implementation processes with  intensive  evaluation  efforts to assess the potential effectiveness of the knowledge broking process in the Fiji context.

The following key organizations  that  have the potential to influence the health of Fiji citizens have been selected and endorsed to participate in this knowledge-exchange process in TROPIC:
1) The Ministry of Health

2) The Ministry of Education

3) The Ministry of Primary Industries (Agriculture)  

4)   The  Ministry   of   Women, Social Welfare and  Poverty Alleviation

5) The Consumers Council of Fiji

6) The Fiji Council of Social Services.  This project is two years into its three year implementation plan, baseline has been collected and intervention programmes are in progress.

Even at these early stages, many lessons have been learned along the way. Establishing networks so that participating organisations can draw from their own strengths come with many challenges, mainly due to the complexity of individual organisation cultures, the substantial capacity building needs, and the time needed to orient all the related organisations towards common goals. The lead times are long and the efforts needed to create the trust and partnerships are substantial, but in the end, it is these relationships which provide the backbone for the programs and their sustainability. Each organisation is different, and this requires substantial flexibility in designing the intervention approach.

CONCLUSIONS
The  TROPIC  project  is  a  complex  research endeavour across six partner organisations. The outcomes of the TROPIC project will guide future obesity  prevention  efforts towards  improving evidence-informed policy-making in all Pacific Island Countries,  and  this will be particularly important  in the Pacific region where obesity prevalence rates are the highest in the world and other  non-communicable  diseases are  a  huge burden on health care resources.

ACKNOWLEDGEMENTS
The authors gratefully acknowledge funding of the research project from AusAID (ADRA grant) and assistance from the Deakin University, partner  organisations and especially the participants, and the support from the College of Medicine, Nursing and Health Sciences in Fiji.

Health Information

Journal, Volume 1 Issue 2 - Evidence based Health Practice

The US Peace Corps Joins the Ministry of Health to Reduce NCDs Through the Promotion of Wellness and Healthy Lifestyles

The United States Peace Corps is a grassroot development organization  founded  by the late President John F. Kennedy in 1961. Peace Corps Volunteers have been working in Fiji since 1968 in all sectors and at all levels.

In late 2011, Peace Corps and the Ministry of Health began discussing a joint partnership to engage in the battle against the increasing incidence of non-communicable disease. The planners believed that prevention of lifestyle- related diseases can be achieved through behavior change brought about by social marketing and the strengthening of the capacity of health workers to promote wellness as part of their overall responsibility as health professionals. After many months of discussion and planning, a project plan emerged with clearly defined and achievable goals and objectives. this project is called the Community Health Empowerment Project (CHEP).

Peace Corps  and  the  Ministry  of Health  will dispatch the first group of 25 Health Promotion Specialist in early November, 2012. They will be assigned to all levels of the Ministry of Health with designated supervisors and counterparts to ensure that skills are transferred and capacity- building   remains   a  priority. Sustainability of any development effort requires a focus on empowering and strengthening existing resources, in this case, the hard working health workers found throughout  the country and the systems that are currently in place.

This project will be monitored on a quarterly basis by a Project Assessment Committee  and adjustments will be made to the project plan as needed. the Health Promotion Specialist make a two-year commitment.  A new group will arrive in  September  of  2013, bringing  the  number of Peace Crops in the field for this project to approximately 50.

Health Information

Journal, Volume 1 Issue 2 - Evidence based Health Practice

PATIENT WAITING TIME IN GOPD AND SOPD AT NADI HOSPITAL 2012

 Author : Lirow Eric , Timaima.B.Tuiketei , Viema Biaukula

ABSTRACT
Patient waiting time is a real problem in Fiji and unfortunately Nadi Sub-divisional hospital is no exception.

The  objective of  this  study  was  to  determine patient waiting  time  in  the GOPD  and  SOPD clinic in the Nadi Sub-divisional Hospital, additionally to gauge patient satisfaction.

Time  logs were given to patients in order to log the time as the patient went through the different management and investigation. Secondly a questionnaire was given to every 20th patient to measure their satisfaction with the services they received in GOPD and SOPD.

The results showed that it took 2 hours  and 57 minutes on average for a patient to be attended by a doctor in the GOPD  clinic and 2 hours and 7 minutes in the SOPD clinic. 50% of all patients sampled believed that there should   be more doctors and 36% complained of the shortage of drugs at the pharmacy.

Any improvement to the quality of health care delivery in   the Nadi Sub-Divisional   hospital needs to include an increase in doctors as well as addressing how to prevent common drug shortages in the pharmacy department.

INTRODUCTION
Patient waiting time is a real problem in Fiji. According to the Fiji Times, Ministry of Health Acting Principal   Administration office Health System Standards Margaret Leong said “Patients gets frustrated because of the long waiting time at hospitals and also because of the attitude of nurses and doctors.  The Ministry   of Health is very serious about customer complaints….we have a complaints policy and risk management in all divisions in the country in order to improve our system.”  (Fiji Times:  49 Nurse Complaints, July 21, 2012).

Fiji Ministry of Health strategic plan for 2011- 2014 states that customer focus remains of major concern. This plan provides the framework for the future planning, management and service delivery by the Ministry of Health to address seven Health Outcomes. These seven Outcomes are derived from the two Strategic Objectives spelt out in the Government’s 2009 – 2014, Roadmap for Democracy & Sustainable Socio‐ Economic Development. And within that Health Outcomes, Ministry of Health has identified several focus areas that we will be specifically targeting in the next 5 years.

Some of the guiding principles are: (1) Vision  – A  healthy population in Fiji  that is driven by a caring health care delivery system. (2)Customer focus –   We are genuinely concerned that health services are focused on the people/patients receiving appropriate high quality health care delivery. (3)Integrity – We will commit ourselves to the highest ethical and professional standards in all that we do. (4) Responsiveness – We will be responsive to the needs of the people in a timely manner,  delivering our  services in  an  efficient and  effective manner.  As  seen in  some  of the guiding principles Fiji  Ministry  of Health wants to reduce waiting time and provide quality health care to the citizens of Fiji.

The   Nadi   Sub   Divisional    Hospital   provides health care services to a total population of around  87,000 at the last census in  2007. Nadi is  multiracial  with  most  of  its  inhabitants  are Indo  Fijians   (53,867),  I taukei    (30,766)  and other  ethnic  groups  (2,367).  It  is   important that the Nadi Hospital be effective and efficient in managing patients in a timely manner.  The GOPD is located as you enter the front entrance of the hospital. It is open during the weekdays from  8:00am to 4:00 pm.  The  arriving  patient would pick a number and waits to see the triage nurse to get the vital signs recorded and assessed if immediate medical attention is needed, if not then the patient sits in the waiting area to be seen by one of the 4 doctors each waiting in  one of the four consultant rooms. If the doctor decides further investigations is warranted such as laboratory or X-Ray then the patient would go to the Scan Room or Pathology lab to be screened. The patient then would wait to be reviewed by the same doctor responsible. And  for patients that the  doctor  decides need further  management then this is done in the treatment room  by the treatment nurse or the doctor themselves. Finally if the doctor prescribes medicine then the patient goes to  the  pharmacy  and  waits  to  get their medication(s).

The SOPD  clinic  is open on the weekdays and this clinic services patients that have been given appointment dates during  their last visit.  There is a nurse and one doctor that attend to all the SOPD patients. The SOPD schedule is as follows: Monday – NCD Clinic; Tuesday – New Cases or referred cases  from  GOPD/AE;  Wednesday  – Hypertensive clinic; Thursday  – Diabetes clinic and Friday – Asthma and psychiatric clinic.

The research question was whether the patients are satisfied with the health services provided by the GOPD/SOPD clinic at the Nadi Hospital. The aim was to determine the waiting time and other related issues in the GOPD/SOPD clinics at the Nadi Hospital from September 1st till October 31st, 2012. The objectives were to determine how long it takes for each patient to be seen at GOPD &SOPD by the different health care workers in the Outpatients department; and to determine if the patients are satisfied with the GOPD &SOPD services provided in the Nadi Hospital.

METHODS:
This is a prospective quantitative study on patient waiting time and patient satisfaction at Nadi Sub Divisional Hospital during September to October 2012 period with two components: time log and a self-administered questionnaire. The purpose of the time log was to determine how long it takes for a patient to be seen at the GOPD &SOPD clinic by the different health care workers in the Outpatients department. Synchronized clocks were placed in these different areas; the triage area, consultant rooms, treatment room, scan room, and pharmacy room. Assistance was sought from the different staffs and doctors to ensure that they log the time the patient arrives. All clocks were checked every morning before the clinics open and when the clinics close to ensure it is all synchronized to the same time.

Time  log: A  time log was given to the patients as they pick a number and wait to see the triage nurse  and it will  be continued to be logged as they go through the different management and investigations warranted. The patient was made aware of the time log and clocks in visible sight and was asked to be mindful to ensure that every staff and doctor log the correct time accordingly. Each  doctor was responsible to put their signature on the time log as they saw the patients. The patient’s information was double checked in every doctor’s GOPD/SOPD  registers. Time logs were not given to the every 20th patient as they were given a questionnaire to fill.

Patients  that  were  time  recorded  were  from 8:00am  to  12:30pm  and  commenced  again  at 3:00pm to 4:00pm to avoid the staff and doctors lunch time which is from 1:00pm to 2:00pm. All time logs were collected before the patients leave the GOPD/SOPD  clinics at a designated area.

Questionnaire: The purpose of the questionnaire was  to determine if  the patients were satisfied with the services provided to them. A self administered   questionnaire  was   presented  to one in every twenty patients seen as they leave the GOPD/SOPD  clinic. The questionnaire was in  the three different languages, English,  Fijian and Hindustani.  The inclusion  criteria were that the patients had  consented, patients presented to GOPD/SOPD  clinics on the weekdays during 8:30am to 4:00pm, all age groups, all gender and ethnicity   and they had to reside in  Nadi were included  in  this  study.  The  exclusion  criteria were those patients that do not consent; relatives, parents or  friends  that accompany  the patient; emergency cases that needed immediate medical attention; patients that do not live within  Nadi Town;  patients that were disabled and  needed assistance to mobilize around; patients that presented after 4:00pm on the weekdays, those that presented on the weekends and patients with a mental condition.

Ethical and confidentiality issues were observed and appropriately addressed with approval obtained from the Ministry  of health to conduct this  study.  Data was  analyzed using  Microsoft excel.

RESULTS:
General Outpatient Department

1. Time Logs:
The  following  results  were  acquired  from  the time logs that were given out for a period of 7 days.

 Overall the total number of patient that came to GOPD clinic was 1,387. The total sample size was 494, giving an overall coverage of 36%,  that this study managed to capture.

Total patients seen at GOPD clinic:
                  

It is important to note the population ratio of i-taukei to Indo-Fijian. Population ratio of the two main ethnic groups in I taukei: Indo-Fijian is 1: 2. Hence this is reflected in the results in the pie chart.

            
 Females made up of 51% (198) and the Males with 192 (49%) of all sampled patients (over 7 days) that presented to GOPD clinic.

The age range of 18-30 years old were mostly seen in this sample size while 0-5yrs made up the least group because these patients do not wait for the triage nurse but goes directly to IMCI clinic.

The i taukei tend to decrease as they get older while Indo-Fijians increase their visits to GOPD. Overall Indo-Fijians made up the most in each age group as expected due to the 2:1 population ratio distribution in the subdivision.

Arrival  to Triage: 47 minutes 38 seconds Triage to Consultation: 2 hours 10 minutes

Time it takes a patient to arrive at GOPD and to see a doctor:

Arrival
 to Consultation: 2 hours 57 minutes

Time it takes to start and complete
each
investigation:

Scan room: 28 minutes 30 seconds Lab
room: 10 minutes 20 seconds Treatment
room: 15 minutes 36 seconds

Time it takes for a patient to be reviewed after being investigated:

Consultation to review: 27 minutes 34 seconds.

Time it takes to give your prescription and receive
your medication(s):

Pharmacy: 8 minutes 23 seconds

The longest time a patient spent in  GOPD  was waiting for a doctor with 2 hours and 57 minutes, starting  from  arrival  time  to  seeing a  doctor.

Followed by the time it takes to be triaged, waiting  47  minutes  for  the  triage nurse.  The third  longest time was  waiting  to be reviewed after  an   investigation,   with   27  minutes.   All the investigation time were acceptable with  an average time  of  18 minutes  for  scan,  lab  and treatment room overall. The shortest time spent in GOPD was waiting 8 minutes waiting for their medications at the Pharmacy.

2. GOPD Patient Satisfaction Questionnaires

Of the total respondents, 52% were Indo-Fijians and  48%  I taukei.  52%  were  males  and  48% females.

                  
64% of all patients sampled were satisfied with the health care service received. 50% of them stated that the waiting time is too long and the GOPD clinic needs more doctors and 36% said that the availability of drugs is a problem in the Nadi Hospital.   These particular   patients explained that they are unable to afford the cost of drugs at the retail pharmacies which will make them noncompliance with their medications. This is reflected in their grading giving the pharmacy the lowest score in the scale of 1 to 5 with 1 being poor and 5 is excellent.

[B] Special Outpatient Department (SOPD)
1. Time Logs:
The  following  results  were  acquired  from  the time logs that were given out for 2 days.
                  

Overall the total number of patient that came to SOPD clinic over two days was 138. The total sample size was 40, giving an overall coverage of 29% that this project managed to capture. 90% of the patients seen were Indo-Fijians and 10% were I taukei. 75% were females and 25% males.

                  
 There were more Indo-Fijians in all the different age groups in this study. The most number seen were in the 56-65 age categories. SOPD clinic was mainly attended by females who make up 30 out of the 40 patients sampled.

 Total of 40 patients sampled out of 138 patients that presented to SOPD clinic (2 days) giving you a 29% coverage that this project managed to capture

Arrival to Triage = 1 hour 37 minutes Triage to Consultation = 30 minutes Arrival to Consultation = 2 hrs. 7 minutes 

The longest waiting time, is the wait to get triaged by the nurse. Upon further investigation, it was revealed that SOPD   goes on an appointment time basis. Despite this fact, most patients would come in 1-2 hours earlier than their appointed times making their waiting time to be triaged longer.

2. SOPD Patient Satisfaction Questionnaires:
67%  of  the  respondents  in  SOPD  clinic  were I taukei and  33% were Indo=Fijians with  67% were females and 33% males. Most of the patients sampled  were  satisfied (67%)  with  the  SOPD health care service.
                  
 When looking at the ratings between pharmacy, nurses and doctors, in a 1 to 5 scale, the pharmacy had the lowest score of 3. The majority of patients responses showed that the drugs they need are mostly  not  available all  the  time  at  the  Nadi hospital pharmacy. These are the NCD clinic drugs, for Diabetes Mellitus 2 and Hypertension treatment.

It is worrying that if these medications continue to be in short supply, there will be poor compliance as patients were not  able to afford them from retail pharmacies, which in the long run is more expensive to  all  concerned when  patients will be admitted or managed on complications that arises from non-compliance.

CONCLUSION:
This   project  has  managed  to  capture  36%  of all patients that came to GOPD  and 29% of allpatients that came to SOPD. GOPD Waiting Time (Arrival – Consultation)  = 2 hours  57 minutes; SOPD  Waiting Time  (Arrival – Consultation)  = 2 hours 7 minutes.
Although most patients were satisfied with the health care services provided in the GOPD & SOPD clinics, 50% complained about the long waiting time so wants more doctors; and 38% said there is shortage of drugs available as they are very expensive to buy at the chemists, which then encourages non-compliance of medication. Triage Nurse needs to have her own Blood Pressure & Glucometer machines and other necessary equipment instead of sharing them with the A&E department.

There is still room for improvement at the Nadi GOPD & SOPD clinics and if these two main complaints are addressed, the MOH will go a long way in providing quality health care services to the residents of the Nadi Subdivision.

ACKNOWLEDGMENT
The  authors  extend  their  sincere  appreciation to SDMO Nadi Dr Eliki  Nanovo and the staff in Nadi  subdivision  for  their  kind  assistance and support in this research, and to the 141 patients who had participated in this study.

Health Information

Journal, Volume 1 Issue 2 - Evidence based Health Practice

MALNUTRITION IN TAVUA SUBDIVISION 2012

 Author:Maurice Atalifo, Timaima.B.Tuiketei  ,Viema.L.Biaukula

ABSTRACT

“Reduce   Child    Mortality”    –    the    fourth Millennium Developmental Goal acknowledges the fact that major causes of child deaths globally is  malnutrition   and  poor  access  to  primary health care and infrastructure. This article aims to   quantify   the   magnitude   of  malnutrition among children 0-5 years of age within the Tavua Subdivision from January 2010 to April 2012.

Methodology:
A  retrospective,  descriptive  and  quantitative study was conducted in order to determine whether  malnutrition was  a  problem  in  the Tavua  Subdivision. Based on  weight for  age, MCH records, Dietician and In-patient Registers were consulted in order to obtain data for this research.

Results and Discussions:
The  prevalence  rate  of  malnutrition   among infants 0-5 years of age in the Tavua Subdivision were found to be 40.6% over a period of 2.33 years or 17.7% per annum were concluded during the period of study. Most of the malnourished cases resided in the peri-urban  and  industrial areas of the subdivision. Among the Indo-Fijian infants, malnutrition was high among infants 0-6 months of age. This was attributed to a high rate of low birth weight. Among the i-Taukei infants, malnutrition   was  high  among  those  greater than 7 months of age. This was attributed to late introduction of solids, poor quality of weaning of food and short weaning processes.

Malnutrition is present in the Tavua sub -division with a prevalence rate of 40.6% over 2.3 years (January 2010 to April 2012) 05 17.7 per year.

Conclusion:
Malnutrition  is common  among Fijian infants compared  to Indo-Fijians. Growth faltering of Fijian children continues to be a problem.

INTRODUCTION
Malnutrition  is a deficiency of nutrition.  It is a serious public-health problem that has been associated with an increase in the risk of child mortality  and  morbidity.  Children   bear  the brunt of the disease burden associated with malnutrition.   Etiologically, many  factors  can cause  malnutrition,   most  of  which  relate  to poor  diet  or  severe and  repeated  infections, particularly in underprivileged populations. Inadequate diet and disease, in turn are closely linked  to  the  general  standard  of  living, the environmental conditions, and whether a population is able to meet its basic needs such as food, housing and  health care.1  From  then international  perspective, the  United  Nations fourth Millennium Development Goals (MDG), acknowledges the fact that causes of child deaths globally are related to malnutrition and the lack of access to adequate primary health care and infrastructure,  such as water and sanitation  in many developing countries – more than a third of all child deaths  were attributable  to  under nutrition.2   Under nutrition in children less than 5 years is an indicator of poverty and hunger.In  line  with  the  MDG’s,  the  government  of Fiji’s Strategic Developmental Plan (2007-2011) focuses on poverty and hunger to address under nutrition.

Tavua  Subdivision is situated  in  the  Western Division and is approximately 90km away from Nadi.6  it is land locked between the Ba and Ra Medical Subdivisions. It  has  a  population  of approximately 27000 with a fair balance between the  2  major  ethnic  groups:  i-Taukei  and  the Indo-Fijian population. The subdivision with a fairly large fertile agricultural land and abundant supply of seafood, there is sufficient food supply with  root   crops,  fruits  and  vegetables. The subdivision is also reach in natural resources with an abundant  supply of mineral water, forestry, cattle grazing and gold.

The Tavua  Medical Subdivision consists of 3 medical areas – Tavua, Vatukoula and Nadarivatu. In each medical area, it is further divided into zones – a total of 10 zones. The Vatukoula Health Centre at the moment is not operational, so all the patients are seen in the Tavua Health Centre instead. Each zone is looked after by a Public Health  Nurse.  Mothers  bring  their  children to  the  Maternal  Child  Health  (MCH)  clinic where a child’s nutritional  status is evaluated, general  body  condition  assessed, diet  history determined,  immunisations  are given and  the child’s development progress is assessed.

The   aim   of   the   study   was  to   determine the presence of Malnutrition in the Tavua Subdivision and to quantify the magnitude of the problem from January 2010 to April 2012. The objectives were to determine the prevalence of Malnutrition in Tavua Subdivision from January 2010 to April 2012; and to discuss the descriptive characteristics of Malnutrition  among children in the Tavua subdivision from January 2010 to April 2012.

Methodology
This   was   a   retrospective,   descriptive   and quantitative study, with approval obtained from MOH, to determine whether malnutrition in the Tavua Subdivision from January 2010 to April
2012.  The MCH daily attendance registers, for all the medical zones in the subdivision were examined. The data was collected from was Tavua Health  Centre,  Nadarivatu  Health  Centre  and the Nadrau Nursing Station. Using the Ministry of Health’s Classification of Malnutrition, a case was determined. This is classified as a percentage of present weight in kilograms for precise age in months. The classification falls into 3 broad categories:(a)Mild: 75-89% of weight for age, (b) Moderate: 60-74% of weight for age, (c) Severe: <60% of weight for age.

The Dieticians Register was also used to obtain data. This was because; the mild and moderate cases were referred to the Dietician for further management.Severe cases of malnutrition  were admitted and treated as in-patients. Ethical issues were appropriately addressed. The projected sample  size  was  1400  malnutrition   children seen in the MCH clinics in Tavua subdivision. The inclusion criteria were children aged: 0-60 months, seen within the period of study, from January 2010 to April 2012 an permanently resided in   Tavua Subdivision. Children above the age of 60 months, not seen during the study period  and  not  permanently  residing  in  the Tavua Subdivision were excluded.

RESULTS AND DISCUSSION
Table 1: Number of Cases obtained from MCH Attendances,  Dietician’s  Register and  the  In- patient Register according to Zone from January 2010 to April 2012.

Table 1 summarises the number of cases seen in the MCH Clinics, the total number of malnourished cases that were identified, the number of cases referred to the dietician and the number of cases admitted to the ward as per zone.

With  a total  of 2537 cases seen at the  MCH clinics from January 2010 to April 2012, based on weight for age, the prevalence of Malnutrition in the Subdivision can be calculated as follows:

The prevalence of malnutrition in the Tavua sub division is 40.6% over a period of 2.3yrs or 17.7% per year. 
                     
With  higher  population  densities in  zones  1,5, 6 and 7, it recorded the highest number  of malnourished cases from January 2010 to April 2012. Located around the urban and industrial area of the Tavua Subdivision, it accounts for 60% (n=617) of the malnourished cases seen at the MCH clinics.

 Figure 2 demonstrates the number of malnourished  cases according  to  the  3 broad categories as per medical zone. Similarly to Figure
1.1, Zones 1, 5, 6 and 7 has the highest record of mild and moderate malnourished cases.

A total of 29 cases of severe malnutrition  were recorded from January 2010 to April 2012, Zone 6 had the highest record 24.1% (n=7) followed by Zones 7 and 2, accounting for 17.2% (n=5) and 13.8% (n=4) of the severely (n=4) infants respectively. Nadrau in the Nadarivatu Medical area recorded 1 case of severe malnutrition. The figure shows that  the severity of malnutrition increases with children that reside in the urban areas and in areas of high population density of the Tavua Subdivision.

 As shown in Figure 3, Fijian infants have the highest   number   of   malnourished   cases  in the  Tavua  Subdivision from  January  2010 to April 2012. It accounts for 57% (n=587) of the total  number  of cases followed by the  Indo- Fijian population  41% (n=423). The minority ethnic  group  had  a  record  of 2% (n=20).  A slight difference was noted  among  the gender distribution  of malnourished  cases (figure 4); Males 52% (n=539) and Females 48% (n=489).

 The feeding pattern of a child as documented in the MCH attendance is grouped into 4 broad categories (Figure 5). 59% (n=783) of all malnourished cases for January 2010 to April 2012  were  breast  fed.  This  was  followed by Mash Diet and Family Food, each respectively recording 18% (n=240) and 12% (n=155). The fourth group is ‘others’ – accounts for 11% (n=148)  of  all  malnourished   cases.  ‘Others’ refers to other forms of artificial feeds such as powder milk, SMA, bottle feed, S26, cow’s milk and Lactogen. The most common type of bottle feed given to a child is Powder milk 27% (n=40) followed by SMA – 20.3% (n=30) and S26 – 8.8% (n=13) respectively.

The figure 7 above displays the age category into 2 broad groups; less than  6 months  and more than 7 months. This is because of the age cut- off for exclusive breastfeeding is 6 months  of age. These 2 age categories are further divided into ethnic groups. The figure shows that most of the malnourished cases for children less than 6 months  are the  Indo-Fijian  children  – 20.4% (n=210), followed by the i-Taukei – 16.9% (n=174). No reasons could be associated with this high number of malnourished cases among the Indo-Fijian population but the NNS 20044 states that Indo-i-Taukei babies has a higher rate of LBW as compared to the i-Taukei babies. It also states that for every i-Taukei baby born with LBW, there will be 2 Indo-Fijian  infants born with LBW.

The  second  age  category  is  infants  that  are more than 7 months to 5 years. Here it is noted that  i-Taukei  infants  exceeds the  number  of malnourished cases when compared to the Indo- Fijians and the minority ethnic group. i-Taukei having 40.1% (n=413), the Indo-Fijians 20.7% (n=213) and the minority ethnic group with 0.7% (n=7). No clear reason can be associated with this high number of malnourished cases among the i-Taukei infants that is more than 7 months but the NNS of 19935 states that although i-Taukei infants were born  with above average weight, their  growth  slowed down  after  3-5  months. The report also states that i-Taukei mothers breastfed their babies for a longer duration  but there problem were a late introduction of solids, poor quality of weaning food and short weaning processes. 
                                        

              Figure  8  portrays  infants  less than  1  month old among the Indo-Fijian population from January  2010 to  April  2012 had  the  highest number of malnourished cases across the types of  under-nutrition,  which  is  mild,  moderate and severe. Within this cohort (cases ˂1 month old), based on previous weight recorded in the MCH attendance, 29% (n=61) had a weight of ˂ 2.5kg. This indicates that based on weight for age, malnourished cases among the Indo-Fijian population  from  January 2010 to  April 2012, 29% had a low birth weight. Out of the 10 cases of severely malnourished in the figure above, 90% (n=9) had a previous recorded weight of ˂ 2.5kg. 2 of the infants were pre-term babies.

 Figure 9 shows the feeding history of the malnourished cases among i-Taukei infants, 7-60 months, from January 2010 to April 2012. Almost half of the malnourished cases were still being breastfed. It was found that out of the 413 cases of undernourished children, 38.3% (n=158) were practicing complementary feeds that is being breastfed and is either This concludes that 61.7% (n=255) of these malnourished cases not given complementary feed’s. NNS – 2004 reports that early records show that malnutrition started to occur at around 6 months of age. This could be attributed to insufficient protein food during the early process of weaning or to the introduction of complementary feeding, particularly amongst i-Taukei infants.

A comparison of the number  of malnourished cases, feeding history  and  age (7-60 months) is made  among  the  i-Taukei  infants.  The age category of 7-60 months is further divided into intervals of 6 months.  It   portrays that  as the child  grows older,  the  number  of breastfeeds decreases. This  concludes  that  there  is  poor complementary feeding among the i-Taukei infants (7-60 months) in the Tavua Subdivision from January 2010 to April 2012.

Table 2: Summary of Comments according to points ‘for’ and points ‘against’ child improvement
        

              Table 2 summarises  the  Dieticians comments in  the  register  according  to  points  “for” and points “against” the improvement of the child’s nutritional  status. It shows that there are more points  noted  by  the  dietician  that  is  against the  child’s  improvement.  Having more  points against the child’s improvement will add to the existing prevalence of malnutrition in the Tavua Subdivision. Points “against” can be summarised as poor social background, poor sanitation and parental negligence being the main factors that affect the child’s improvement. 

              In total, there were 7 admissions of malnourished cases into hospital from January 2010 to April 2012. With a relative small number of admissions, the patient demographics and other details are summarised  as  four  females, three  males  of which 5 i-Taukei and 2 Indo-Fijians. Average age of admission is 15 months, 70% of admissions reside in the urban areas of the Subdivision. The average length of stay in hospital was 8 days.
The limitations of this study were: (i) the inability follow up on babies who defaulted their clinic over the period of study that is from January 2010 to April 2012; (ii) Marital Status is not included in the raw data, because this could be a factor related to why the child is malnourished;  (iii) there is no mention of what parents do or work they do – socioeconomic status, as this could be a factor related to their nutritional status.

CONCLUSION
Malnutrition is present in the Tavua sub -division with a prevalence rate of 40.6% over 2.3 years (January 2010 to  April 2012). Malnutrition  is common   among  Fijian  infants  compared  to Indo-Fijians. Growth faltering of Fijian children continues to be a problem.

              
Based on the results above, some of the recommendations are: (1) to improve infant and
 child feeding practice: by enhancing  exclusive breast feeding through promotion, support groups; supporting, strengthening and expanding the ‘Baby Friendly Hospital and work initiatives’; promoting initiatives on the introduction of appropriate   nutritious   complementary   foods. (2) Improve  growth  monitoring:  through regular MCH clinic attendance, training health workers to follow-up infants whose growth starts faltering and to provide appropriate advice. (3) Reduce the incidence rate of Low-Birth Weight babies: through advising mothers on early ante- natal bookings to allow for early detection and correction of dietary problems such as anaemia and other  comorbidities improves baby’s birth weight.

The authors extend their sincere appreciation to the Fiji Ministry of Health for the kind approval and  to  SDMO  Tavua-  Dr  Nadeem  Farooq, Dr  Alumita Serutabua and  the  staff of Tavua Subdivision for their kind assistance and support in this study.

Health Information

Journal, Volume 1 Issue 2 - Evidence based Health Practice