Health Literacy Survey - Deputy Prime Minister · La Primavera by Botticelli The Allegory of Spring is a very refined work of art. The naturalistic details of the meadow, the skilful

Report compiled by the National Statistics Office on behalf of the Office of the Commissioner for Mental Health within the Ministry for Energy and Health

Health LiteracySurveyMalta 2014

Office of the Commissioner forMental Health

La Primavera by BotticelliThe Allegory of Spring is a very refined work of art. The naturalistic details of the meadow, the skilful use of the colour, the elegance of the figures and the poetry of the whole, have made this important and fascinating work celebrated all over the world.

Leaving out the many possible interpretations proposed by various experts, what is certain is the humanistic meaning of the whole work: Venus is the goodwill, as she distinguishes the material (right) from the spiritual values (left). The Humanitas promotes the ideal of a positive man, confident in his abilities, and sensitive to the needs of others.

http://www.uffizi.org/artworks/la-primavera-allegory-of-spring-by-sandro-botticelli/


Collaborating PartnersDr John M Cachia; Commissioner CMHDr Miriam Camilleri; Consultant, Public Health CMHMs Natasha Barbara; Assistant Director, CMHProfs Kristine Sørensen; University of MaastrichtMr Emmanuel Cachia; responsible for the Maltese translation of questionnaireMr Etienne Caruana; Director Social Statistics, NSOMs Joslyn Magro Cuschieri; Manager Labour Market, NSOMs Maristelle Darmanin; Statistician, NSOMr Mario Micallef; Statistician, NSO

SummaryThis report describes the findings of the European Health Literacy Survey (EU-HLS) that was undertaken in Malta in 2014 as part of the follow-up of initiatives linked to the European Year dedicated to Citizenship.

It recommends that Health Literacy (HL) should be integrated in policy making and practice to ensure health equity, citizen empowerment and patient centred care.

The original European Health Literacy Project was conducted by an EU Consortium under the leadership of Maastricht University with eight associated research partners from Austria, Germany, Poland, Greece, Ireland, Bulgaria, Spain and the Netherlands. Many other countries have subsequently joined this project by undertaking the survey. By adopting the same tool devised by the Consortium, in 2014, Malta too joined the other member states and conducted the survey among adults within the Maltese population.

The report presents results for Malta of the EU-HLS 16, the abridged version of the original survey questionnaire. Section 2 is a description of the sampling techniques adopted and the methodology used in this analysis. The main findings have been outlined in Section 3. Section 4 examines the correlation between health behaviours/outcomes and the level of HL. Section 5 provides details on the relevance of the social gradient for HL levels. Section 6 highlights the sub groups of the population that were found to have increased risk of low levels of HL. Section 7 examines the correlation between HL and health service use. The Maltese and English versions of the questionnaire used in this survey can be found annexed to the report.

We believe that this report should be considered as the start of the work on HL in Malta. Further analysis of the information collected in this study is bound to influence the direction of future health policy direction and strategic decisions.

Office of the Commissioner for Mental Health 5

ContentsSummary 5

Abbreviations 8

Foreword 9

1.0 Introduction 10

2.0 Survey and Sample Characteristics 11

3.0 Health Literacy Indices 12 3.1 Main Findings 15 3.2 Comparative analysis 26 3.3 Further examinations 28

4.0 Health Literacy associated with Body Mass Index, self assessed health and long term illness 30 4.1 Body Mass Index 30 4.2 Self-Assessed Health Status 32 4.3 Long term illnesses 33

5.0 The Importance of the Social Gradient for Self-Perceived Health 35

6.0 Proportions of Limited 39 Health Literacy in 39 Vulnerable Populations 39

7.0 Health Service Use: Emergency Services, Hospitals, Doctors and Other Health Professionals – Percentages and Associations 43 7.1 Emergency Services 43 7.2 Hospital Service Use 44 7.3 Doctor Visits 45 7.4 Other health professional services 46

8.0 Conclusion 48ANNEX 1 49 HLS-EU - Q16 - MALTI 49ANNEX 2 50 HLS-EU - Q16 - ENGLISH 50

Design & Printing: Veritas Press Żabbar

Table 1: Percentage distribution of responses for HL statements 12

Table 2: Likert statement used for each Health Literacy dimension 14

Table 3: General Health Literacy Index (GHL) 16

Table 4: General HL index by socio-demographic variables 17

Table 5: Percentage distribution of Health Literacy level* 18

Table 6: Health Literacy index for Health Care, Disease Prevention & Health Promotion 19

Table 7:Socio-demographic variables classified by HL indices for Health Care, for Disease Prevention and for Health Promotion

22

Table 8:

GHL (General Health Literacy), FHI (Finding health information), UHI (Understanding Health information), JHI (Judging health information) and AHI (Applying Health information) indices

23

Table 9: Socio-demographic variables classified by mean scores for FHI, UHI, JHI and AHI 25

Table 10:Descriptive Statistics and Percentiles for General Health literacy, Health Care, Disease Prevention and Health Promotion indices

26

Table 11: Comparative distribution of HLS score 27

Table 12: T test on mean GHL scores with EU figures 27

Table 13: Wilcoxon Signed rank test for indices 28Table 14: Wilcoxon Signed rank test for indices 29

Table 15: Spearman Correlation coefficient for HL indices 29

Table 16: Distribution of BMI by Mean Health Literacy level** 31

Table 17: Distribution of BMI by Mean Health Literacy level and gender* 31

Table 18: Distribution of Self assessed health by Mean Health Literacy level** 33

Table 19:Distribution of long term illness frequency by General Health Literacy level

34

Table 20: Distribution of population by financial deprivation elements* 35

Table 21: Distribution of population by net monthly household income 36

Table 22: Mean HL levels for financial deprivation elements and household net income** 37

Table 23: Distribution of income by difficulty to pay bills 38

Table 24: Percentage of persons with limited HL in very vulnerable groups* 39

Table 25:Comparative analysis in the percentage of individuals with limited general Health Literacy in very vulnerable groups*

40

Table 26:Percentage of individuals with limited general Health Literacy in vulnerable groups*

41

Table 27: Comparative analysis of individuals with limited general HL in vulnerable groups* 42

Table 28: GHL index by frequency of emergency service use 44

Table 29:Distribution of persons by frequency of emergency service use and dimensions of Health Literacy

44

Table 30:Distribution of persons by frequency of hospital service use and dimensions of Health Literacy

45

Table 31:Distribution of persons by frequency of doctor visits and dimensions of Health Literacy

46

Table 32:Distribution of persons by frequency of other health professional visits and dimensions of Health Literacy

47

Table 33: Cross Correlations between Indicators for Health Service Use 47

Tables

Figure 1: Population distribution by level of HL 15

Figure 2: Distribution of the population by level of HL for Health Care 19

Figure 3: Distribution of the population by level of HL for Disease Prevention 20

Figure 4: Distribution of the population by level of HL for Health Promotion 21

Figure 5: Body Mass Index frequencies 30

Figure 6: Distribution of Self assessed health 32

Figure 7: Distribution of the population by prevalence of long term illnesses 33

Figure 8: Limitations of activities from health problems 34

Figure 9: Emergency services frequencies 43

Figure 10: Hospital service frequencies 44

Figure 11: Doctor visits frequencies 45

Figure 12: Other health professional visits frequencies 46

Figures


AbbreviationsHL - Health LiteracyEU-HLS - European Health Literacy SurveyHLS - Health Literacy SurveyCATI - Computer Assisted Telephone InterviewingFHI - Finding Health InformationUHI - Understanding Health InformationJHI - Judging Health InformationAHI - Applying Health InformationGHL - General Health LiteracyHC - Health CareDP - Disease PreventionHP - Health PromotionBMI - Body Mass Index


Foreword

F ollowing recommendations by representatives from the University of Maastricht in 2013, the Office of the Commissioner for Mental Health commissioned the National Statistics Office to undertake this study with the aim of measuring the HL level of the Maltese population. Our particular interest was to understand better the HL level of persons with mental disorder and to be better equipped to address their needs. The measuring instrument that was adopted consisted of a questionnaire that was constructed by the EU-HLS Consortium and used to measure the level of HL in eight European Union Member States in 2011. The results obtained are comparable to those obtained in other EU Member States.

This report provides a general health literacy profile of the Maltese Population across socio-demographic characteristics. We analysed health literacy levels for the three domains of the health system: health care, disease prevention and health promotion. The most significant finding was that nearly half of the Maltese adult population have problematic or inadequate levels of HL. Moreover 45.7% have difficulty or do not know where to find information on how to manage very common mental health problems like stress and depression. The study identified vulnerable groups within the population at high risk of low health literacy level. Our task is to explore ways of how these findings can be addressed or mitigated.

HL is strongly emerging from the margins to the mainstream of European and international debates on health. This study is just the beginning of local work in the area of HL. We strongly believe that further work and analysis will influence the direction of future policy and service provision decisions within our health system. There is valuable evidence for targeting vulnerable groups in order to improve lifelong health outcomes through personalised approaches and person-centred interventions.

Through this study, my Office is providing a strong effective strategic tool. This will be useful for practitioners and researchers at practice and policy levels to be better equipped to address, protect and uphold the rights of the most vulnerable persons in society.

I thank the small team at my Office for their hard work and professionalism.

John M. CachiaCommissioner for Mental Health

1.0 Introduction

T he HLS for Malta was conducted in July 2014 by the National Statistics Office on behalf of the Office of the Commissioner for Mental Health within the Ministry for Energy and Health. A stratified random sample of persons aged 18 years and over was selected for this survey. In total, information from 1,514 persons was gathered using a standardised questionnaire through the use of Computer Assisted Telephone Interviewing (CATI).

The model for this survey was derived from the EU-HLS conducted in eight European countries*1 during summer 2011. The short version of the EU-HLS tool, HLS-EU-Q162, was used. This version containing a total of 16 statements was prepared by the HLS-EU Consortium as a result of the analysis of the Health Literacy Survey (HLS) data which used the original tool that contained 47 statements. These statements covered Health Care, Disease Prevention and Health Promotion. Three main areas were assessed for four processing information stages, namely access to health information, understanding information provided, evaluating information provided and acting upon this information. Each respondent was asked to give his/ her opinion on a 4 point Likert scale (very easy, fairly easy, fairly difficult, very difficult). Those interviewed had a fifth option (don’t know) which was discarded for the purpose of reporting most of the results. National results can be compared with the mean of the 8 countries which conducted this survey in 2011.

In compiling the findings of the national HLS , the Office of the Commissioner for Mental Health used a harmonised methodology that was applied by the eight EU member states so that national findings could be compared to those of the other countries which conducted this enquiry.

Throughout the report, under-represented values (i.e. estimates based on less than 30 sample readings) are indicated in a bold font. Readers are therefore strongly advised to interpret under-represented figures with caution.

1 Austria, Bulgaria, Germany (North Rhine-Westphalia), Greece, Ireland, Netherlands, Poland, and Spain

2 HLS-EU Consortium (2012): HLS-EU-Q16. The European Health Literacy Survey Questionnaire – short version

“Three main areas were assessed for four processing stages, namely access to health information, understanding information, evaluating information and acting upon this information.”

Health Literacy Survey Malta10

2.0 Survey and Sample Characteristics

T he target population of the HLS was made up of individuals who were 18 years and over and living in private households. A stratified random sample based on district, age group (18-32, 33-48, 49-64 and 65+) and gender was selected. Quotas were applied on the strata in order to obtain a fully representative net sample of 1,500 persons.

The questionnaire used for this survey is provided in Annex A of this document. The first part of the survey included 16 statements, followed by a number of questions related to health in general and socio-demographic variables, derived from the original extended matrix and concept-related version of the tools developed by the HLS-EU Consortium.3

Data collection took place during weekdays between 4pm and 8pm and on Saturdays between 9am and midday, during the period of 2nd to 31st July 2014. A total of 18 interviewers were engaged for the purpose of this exercise.

Following the data collection, all information was extracted and analysed using appropriate statistical software. Specific weights were worked out in order to gross up results to the whole household population. The weighting methodology consisted of post stratification based on gender, age group and district of residence of respondents.

3 HLS-EU Consortium (2011): HLS-EU-Q86. Office of the Commissioner for Mental Health 11

3.0 Health Literacy Indices

The distribution based on the Likert scale for each statement that was used for the HLS survey is shown in Table 1.

On a scale from very easy to very difficult, how easy would you say it is to:

Very Easy

Fairly Easy

Fairly Difficult

Very Difficult

Don’t Know

1 find information on treatments of illnesses that concern you 23.8% 56.7% 15.8% 0.5% 3.2%

2 find out where to get professional help when you are ill 26.0% 60.8% 11.6% 0.3% 1.3%

3 understand what your doctor tells you 25.4% 61.6% 11.5% 0.2% 1.3%

4 understand your doctor’s or pharmacist’s instructions on how to take a prescribed medicine 28.0% 64.4% 6.8% 0.5% 0.5%

5 judge when you may need to get a second opinion from another doctor 15.5% 54.0% 24.9% 2.4% 3.2%

6 use information the doctor gives you to make decisions about your illness 28.8% 59.5% 9.3% 0.3% 2.1%

7 follow instructions from your doctor or pharmacist 31.8% 62.8% 4.3% 0.3% 0.7%

8 find information on how to manage mental health problems like stress and depression 10.0% 44.3% 30.6% 2.3% 12.8%

9 understand health warnings about behaviour such as smoking, low physical activity and drinking too much 40.2% 52.3% 5.7% 0.8% 1.0%

10 understand why you need health screenings 34.2% 54.1% 9.8% 1.2% 0.7%

11 judge if the information on health risks in the media is reliable 16.5% 48.5% 28.2% 1.5% 5.3%

12 decide how you can protect yourself from illness based on information in the media 13.8% 48.2% 31.1% 2.0% 4.9%

13 find out about activities that are good for your mental well-being 19.9% 50.7% 21.4% 2.4% 5.7%

14 understand advice on health from family members or friends 18.8% 51.6% 25.4% 2.1% 2.2%

15 understand information in the media on how to get healthier 11.6% 59.2% 24.1% 1.1% 4.0%

16 judge which everyday behaviour is related to your health 30.0% 57.0% 11.0% 0.8% 1.1%*Under-represented values (sample counts of 29 or less) are highlighted in bold font.

Table 1: Percentage distribution of responses for HL statements*


Analysing each question, it is evident that for all of the sixteen statements identified in table 1, the majority of respondents felt that the issues being asked were ‘Fairly easy’ or ‘Very easy’ to handle. In fact, more than half of the statements (1-4, 6, 7, 9, 10, 16) had a share of more than 80% within these two categories combined. The lowest rates were obtained for statements 8 (54.3%), 12 (62.0%) and 11 (65.0%).

The lowest responses for both the ‘Very Easy’ and ‘Fairly easy’ options were for the statement relating to mental health problems (statement 8). In this regard, it is estimated that only 10% and 44.3% of the population found it ‘very easy’ and ‘fairly easy’ respectively to find information on how to manage mental health problems. This statement on mental HL elicited also the highest ‘don’t know’ response (12.8%) and the second-highest ‘fairly difficult’ response(30.6%).

The highest response where persons stated that they find it ‘fairly difficult’ (31.1%) was related to application/use of information given in the media on how to protect oneself from illnesses (statement 12).

The overall HL is determined by the combination of the way respondents answered to statements associated with Health Care (HC), Disease Prevention (DP) and Health Promotion (HP) mentioned in Table 1. These dimensions were in turn combined to how respondents answered to statements associated with access to information finding health information (FHI), understanding health information (UHI), judging health information received (JHI) and applying health information provided (AHI). Table 2 provides the links between the different dimensions. The combination of the sixteen statements in turn yielded the General HL (GHL) index.

Each of the three main areas had a sub index based on mean values of GHL items. The matrix below provides the distribution of Likert scale statements by sub-dimensions of HL.

“The majority of respondents felt that the issues being asked were

‘Fairly easy’ or ‘Very easy’ to handle.”


Using the table above, Health Literacy (HL) with respect to Health Care has been determined through seven statements, Disease Prevention was determined through five statements whereas Health Promotion had four statements. Each statement which was addressed in the national questionnaire was given a numeric value with statements rated by respondents as being ‘very difficult’ as having a numeric value of ‘1’ and statements being rated as ‘very easy’ as having a numeric value of ‘4’. Statements which were answered as ‘Don’t know’ were not given any value in order not to bias results. For each respondent, the average value of all statements (excluding those statements with a ‘Don’t know’ answer) was worked out and then converted to a metric score in order to obtain the relevant HL index. The following formula4 was applied:

Index = (Mean -1) * (50/3)Where: Index… is the specific index calculated Mean… is the mean of all participating items for each Individual 1 ………… is the minimal possible value of the mean (leads to a minimum value of the index of 0) 3 ……… is the range of the mean 50…… is the chosen maximum value of the new metric.

Metric scores for HL indices ranged between ‘0’ and ‘50’ with ‘0’ being the least value and ‘50’ the maximum.

The same method was applied when working out indices to determine the processing of information stages, namely, FHI, UHI, JHI, AHI.

4 Page 22 of HLS-EU CONSORTIUM (2012): COMPARATIVE REPORT OF HEALTH LITERACY IN EIGHT EU MEMBER STATES. THE EUROPEAN HEALTH LITERACY SURVEY HLS-EU , ONLINE PUBLICATION: HTTP://WWW.HEALTH-LITERACY.EU

Table 2: Likert statement used for each HL dimension

HL FHI UHI JHI AHI Totalstatements

HC 1, 2 3,4 5 6,7 7DC 8 9,10 11 12 5HP 13 14,15 16 - 4

Total statements 4 6 3 3 16

* Finding Health Information (FHI), the understanding of information (UHI), the judgement of information (JHI) and the application of information relevant to health (AHI).


The GHL index was tested for normality using the one sample Kolmogorov-Smirnov test, which showed that this variable was not normally distributed. Consequently, non- parametric tests were used throughout the report.

Respondents having a score of 25 or less were categorised as having ‘inadequate’ HL, persons scoring between 25 and 33 were deemed to have ‘problematic’ HL whereas individuals with a score of 33 to 42 were assumed to have ‘sufficient’ HL. Persons obtaining a score of 42 to 50 were deemed to have an ‘excellent’ level of HL.

3.1 Main Findings

The results in Figure 1 show that 9.2% had an excellent level of HL, which, however, is less than the mean share obtained for the 8 countries which carried out the EU-HLS (EU-HLS – 16.5%). Those who had ‘sufficient’ and ‘problematic’ HL levels made up a larger proportion of the population when compared to the results published in the EU-HLS. In fact, in the EU study these made up 36.0% and 35.2% respectively. However persons with an ‘inadequate’ HL score made up 3.3% of the total, as compared to 12.4% in the EU study.

Figure 1: Population distribution by level of HL

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

%

Inadequate Problematic Sufficient Excellent

42.5

45.0

9.23.3


The overall national mean and median GHL index were estimated to be 34.0 and 33.3 respectively. As Table 3 illustrates differences in the General Health Literacy (GHL) levels between males and females are marginal.

A cross tabulation of the GHL by other socio-demographic variables is provided in Table 4 below. The Independent Sample Kruskal-Wallis Test did not reveal any significant differences in the GHL characteristics (distributions) between different age groups, genderes, persons of different marital status or district. In addition no significant differences were observed among different types of households, households with or without children or persons with a different self assessed social status.

Statistically significant changes were on the other hand observed between persons having different levels of education. In this regard persons who had a tertiary level of education resulted to be more literate than those who had lower levels of education. This conclusion also applied to the male population as the annotations in Table 4 suggest. Differences were also observed among persons with different labour status, with the ‘unemployed’ resulting to have better literacy scores when compared to other subgroups. These findings are further corroborated in Tables 6 and 7.

Table 3: GHL Index

Mean General Health Literacy Index

Male 34.06

Female 33.94

Total 34.00

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.


Table 4: GHL index by socio-demographic variablesMean GHL index

Male Female Total

Age Group

Less than 25 34.18 33.68 33.94

26-35 33.77 33.86 33.82

36-45 33.95 33.97 33.96

46-55 34.41 34.52 34.46

56-65 33.78 34.27 34.04

66-75 34.12 34.22 34.18

76 and over 34.72 31.52 32.92

District

Southern Harbour 34.06 33.14 33.60

Northern Harbour 34.05 34.44 34.25

South Eastern 33.31 34.41 33.85

Western 35.33 33.40 34.34

Northern 34.03 34.12 34.08

Gozo and Comino 33.35 33.40 33.37

Education Levels

Primary or less 33.35* 33.17 33.25*

Secondary 33.81* 33.89 33.85*

Post Secondary 34.18* 34.78 34.48*

Tertiary 35.16* 34.13 34.65*

LabourStatus

Employed 33.96 34.17* 34.03*

Unemployed 35.23 39.31* 37.63*

Retired 33.88 33.57* 33.77*

Other inactive 34.35 33.30* 33.54*

Household status

Living alone 34.22 32.24 33.02

Household made up of more than one person 34.04 34.10 34.07

Children in the household 1

Presence of children in the household 34.08 34.20 34.15

No children in the household 33.95 33.68 33.82

Marital status

Single (not married) 34.00 33.54 33.79

Married 34.00 34.23 34.11

Divorced/ Separated 34.98 33.76 34.36

Widow 34.83 33.17 33.40

Self assessed social status

Low 33.88 34.39 34.16

Middle 34.10 33.74 33.92

High 34.19 34.54 34.351 In the context of this study there was no age threshold for children* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.


Table 5: Percentage distribution of HL level* (under represented values of sample counts ≤ 29 in bold font) Health Literacy (%) Inadequate Problematic Sufficient Excellent

Gender

Male 3.6% 41.4% 45.7% 9.3%

Female 3.0% 43.7% 44.2% 9.1%

Total 3.3% 42.5% 45.0% 9.2%

Age Group

Less than 25 3.2% 43.8% 43.2% 9.8%

26-35 3.0% 44.2% 45.0% 7.8%

36-45 3.2% 45.8% 40.7% 10.3%

46-55 3.0% 38.3% 48.8% 9.9%

56-65 3.3% 40.2% 49.5% 7.0%

66-75 2.7% 40.8% 44.4% 12.1%

76 and over 6.5% 47.9% 38.2% 7.4%

District

Southern Harbour 6.2% 43.5% 42.6% 7.7%

Northern Harbour 2.3% 39.8% 48.6% 9.4%

South Eastern 2.2% 46.2% 42.4% 9.2%

Western 3.4% 40.4% 43.7% 12.5%

Northern 2.6% 40.0% 49.4% 7.9%

Gozo and Comino 3.4% 52.6% 35.1% 8.8%

Education Levels

Primary or less 5.4% 43.4% 43.3% 7.8%

Secondary 3.3% 43.9% 44.8% 8.1%

Post Secondary 2.6% 40.6% 45.2% 11.5%

Tertiary 1.8% 40.4% 46.8% 11.0%Children in the household (no age threshold)

Presence of children in the household 3.0% 41.1% 47.4% 8.6%

No children in the household 3.7% 44.2% 42.1% 9.9%

Marital status

Single (not married) 4.6% 41.5% 45.0% 8.9%

Married 2.7% 42.9% 45.2% 9.2%

Divorced/ Separated 3.5% 40.1% 47.6% 8.8%

Widow 3.3% 47.8% 39.5% 9.5%

Household status

Living alone 3.8% 47.1% 41.8% 7.4%

Household made up of more than one person 3.3% 42.3% 45.2% 9.3%

Labour Status

Employed 3.2% 43.6% 44.2% 9.1%

Unemployed 1.4% 23.4% 49.5% 25.7%

Retired 5.3% 40.5% 45.3% 9.0%

Other inactive 2.8% 45.1% 44.9% 7.1%

Self assessed social status

Low 3.3% 48.5% 34.1% 14.1%

Middle 3.2% 42.3% 46.3% 8.3%

High 3.0% 40.6% 46.0% 10.4%


Table 5 illustrates the percentage distribution of HL levels by different socio-demographic variables. The distribution reflects the percentage distribution for the different levels of GHL. A more detailed breakdown for this index was not possible due to limitations associated with small sample size.

Further analysis is being provided by sub-dimensions of HL, namely, for health care, for disease prevention and for health promotion.

Table 6: Health Literacy index for Health Care, Disease Prevention & Health Promotion

GHL Index HC Index DP Index HP Index

Mean 34.01 34.81 31.48 31.67

Figure 2: Distribution of the population by level of HL for Health Care

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%


6.0

28.3

46.3

19.4

As regards to Health Care, the majority of the population (46.3%) was estimated to have ‘sufficient’ HL, followed by those with ‘problematic’ HL (28.3%). Persons with ‘excellent’ and ‘inadequate’ levels of HL made up 19.4% and 6.0% of the total respectively. These results compared better


0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%

with those registered among the eight European countries where 39.1% of respondents were recorded to have ‘sufficient’ HL and 12.1% had ‘inadequate’ HL for health care. The share of persons with excellent and problematic HL compared almost identically to Malta’s results with 19.9% and 28.8% respectively in the EU-HLS.


20.0

29.0

40.3

10.7

Figure 3: Distribution of the population by level of HL for diseasep prevention

Locally there were less people with ‘excellent’ HL on Disease Prevention (10.7%) when compared to the average of those interviewed in the EU-HLS (21.3%). The majority of the population had ‘sufficient’ HL on Disease Prevention (40.3%) whilst those categorised as having a ‘problematic’ level of HL compared almost identically with the average of those interviewed in the EU-HLS (29.0%). On the other hand, Malta had a higher prevalence of people with ‘inadequate’ HL for Disease Prevention when compared to the EU-HLS (13.7%).


0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%

Figure 4: Distribution of the population by level of HL for health promotion

Nearly half of the surveyed population had ‘sufficient’ HL for Health Promotion while one third (33.1%) were found to have a ‘problematic’ level of HL for Health Promotion. Subsequently those categorised as having ‘inadequate’ HL made up 11.1% of the total population whereas the remaining 6.8% were deemed to have an ‘excellent’ level of Health Promotion HL. By comparison EU-HLS results were: inadequate (20.1%), problematic (30.8%), sufficient (33.5%) and excellent (15.6%).


11.1

33.1

49.1

6.8


Table 7: Socio-demographic variables classified by HL indices for health care, for disease prevention and for health promotion

Health Care Index

Disease Prevention

Index

Health Promotion

Index

Age Group

Less than 25 35.88 33.31 30.59*26-35 35.1 32.22 31.19*36-45 35.21 31.16 31.79*46-55 35.34 31.94 32.78*56-65 34.87 31.49 31.65*66-75 34.56 31.92 32.89*

76 and over 33.59 30.76 30.27*

District

Southern Harbour 35.00 31.39 30.98Northern Harbour 35.50 31.92 31.94

South Eastern 35.00 32.10 31.42Western 34.73 32.39 32.72Northern 35.15 32.45 31.74

Gozo and Comino 34.23 31.06 30.56

Education Levels

Primary or less 34.24* 31.17* 31.67Secondary 34.66* 31.53* 31.55

Post Secondary 35.62* 32.86* 31.89Tertiary 36.34* 32.49* 31.87

Labour Status

Employed 35.10* 32.07* 31.75Unemployed 40.48* 36.03* 33.68

Retired 34.40* 31.47* 31.43Other inactive 34.57* 31.25* 31.47

Children in the household1

Presence of children in the household 35.17 31.68 32.07No children in the household 35.06 32.05 31.3

Marital status

Single (not married) 35.37 31.98 31.06

Married 34.94 31.83 31.93Divorced / Separated 35.53 32.60 32.48

Widow 34.48 31.40 31.79

Household status Living Alone 34.35 30.53 32.21

Household made up of more than one

person35.14 32.00 31.66

Self assessed Social status

Low 35.80 31.85 31.46Middle 34.99 31.69 31.64High 35.22 33.27 32.62

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.1 In the context of this study there was no age threshold for children


From Table 7, it was noted that the indices for the three different dimensions of health for the different sub groups of the population were marginally different from each other. As a result, in order to determine whether such differences were significantly different, the Kruskal-Wallis test was applied. The test results concluded that the characteristics (distributions of responses) for the three mentioned indices were different across age groups. This implies that among the different age groups, persons between 66 and 75 years resulted to be the most literate on health promotion, followed by those between 46 and 55.

HL levels increase with increasing levels of education for both Health Care and Disease Prevention. Persons with tertiary education and persons with a post-secondary level of education had better health-care HL levels than persons with lower levels of educational attainment. For HL for disease prevention, persons with a post-secondary level of education resulted to have a better index than all other education sub-groups.

Through the Kruskal-Wallis test, significant differences in Health Care and Disease Prevention were also observed in the population when classified by labour status. From the figures presented in Table 7, the ‘unemployed’ followed by the ‘employed’ had the highest HL levels for both Health Care and Disease Prevention. In fact, persons who were ‘unemployed’ have the highest levels for both indices.

Figures on indices for HL which reflect the modes of dealing (find, understand, judge, apply) with health relevant information as measured through FHI , UHI, JHI and AHI are being provided in Tables 8 and 9.

Table 8: GHL indices for FHI, UHI, JHI & AHI

GHL Index

FHI Index

UHI Index

JHI Index

AHI Index

Mean 34.01 30.96 34.58 31.63 33.86* Finding Health Information (FHI), the understanding of information (UHI), the judgement of information (JHI) and the application of information relevant to health (AHI).


Results from this study reveal that indices for FHI and for JHI differed by age group. This was also proved by the Kruskal-Wallis test, as shown above. Persons aged 25 or less had the highest FHI index and this index was found to decrease with increasing age. Indices for JHI increased with increasing age with persons in the age range of 46 till 55 years having the highest JHI.

In terms of educational attainment, significant differences have been recorded in FHI, UHI and AHI. In this regard, persons with a tertiary level of attainment were estimated to be the group with the highest levels for these dimensions. When analysing the information by labour status of the population, significant differences for the same dimensions, namely, FHI, UHI and AHI were also found. Once more, significant differences were recorded among the ‘unemployed’ category followed by the ‘employed’. In fact these sub groups resulted to be more literate in terms of FHI, UHI and AHI.

Further significant differences were found in the mean levels of JHI, whereby households with children resulted to have better scores (32.0) for this dimension than those with no children (31.5). In interpreting this finding one must bear in mind that for the purpose of this study no age threshold for ‘children’ was set.


Table 9: Socio-demographic variables classified by mean scores for FHI, UHI, JHI and AHIFHI UHI JHI AHI

Age Group

Less than 25 33.13* 34.81 30.62* 34.6926-35 31.90* 34.48 31.46* 33.8936-45 31.69* 34.55 31.33* 34.0246-55 31.15* 35.10 33.44* 34.5156-65 30.05* 34.92 32.04* 34.1666-75 30.58* 35.20 32.29* 34.56

76 and over 29.57* 33.90 30.59 32.04

District

Southern Harbour 30.75 34.53 31.70 33.38Northern Harbour 31.33 34.99 32.19 34.68

South Eastern 31.60 34.41 31.74 34.13Western 31.55 35.10 31.92 34.57Northern 31.61 35.10 31.91 33.92

Gozo and Comino 30.50 34.03 30.00 33.83

Education Level

Primary level or less 30.24* 34.42* 31.15 33.91*Secondary 30.90* 34.36* 31.73 33.85*

Post Secondary 31.78* 35.48* 32.34 34.41*Tertiary 32.63* 35.42* 32.00 34.88*

Labour Status

Employed 31.83* 34.68* 31.60 34.16*Unemployed 35.54* 38.68* 35.21 38.64*

Retired 29.30* 35.01* 31.71 33.80*Other inactive 30.82* 34.22* 31.60 33.65*

Household status

Living Alone 30.53 34.19 31.46 33.99Household made up of more than one person 31.33 34.83 31.82 34.17

Children in the

household 1

Presence of children in the household 31.32 34.86 32.03* 34.26

No children in the household 31.31 34.71 31.47* 34.08

Marital status

Single (not married) 31.73 34.61 31.15 34.25Married 31.08 34.82 32.07 34.06

Divorced / Separated 32.11 34.97 32.68 35.08Widow 29.86 35.24 31.17 33.85

Self assessed Social status

Low 31.51 34.91 31.89 34.70Middle 31.04 34.66 31.86 34.06High 32.56 35.53 31.72 34.70

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.1 In the context of this study there was no age threshold for children


3.2 Comparative analysis

Table 10 gives an overview of the descriptive statistics related to the four HL indices.

In order to determine the accuracy of the point estimates, the margins of error were worked out for each of the main variables, as shown above. This was done in order to determine the interval around x in such a way to know whether there is a large probability that the actual mean falls inside of this interval.

For instance, when considering GHL, the 95% confidence interval for the mean index worked out to be between 33.7 and 34.3. This implies that the values in the interval all lie within the ‘sufficient’ general HL category given that they lie between the range of 33 and 42.

In Health Care, 95% confidence interval for the mean index is between 34.5 and 35.2. This implies that the values in the interval all lie within the ‘sufficient’ general HL category since the values lie between the range of 33 and 42.

Table 10: Descriptive Statistics and Percentiles for GHL, health care, disease prevention and health promotion indices

GHL Index Health Care Index

Disease Prevention Index

Health Promotion Index

Range 45.83 45.24 50.00 50.00Minimum 4.17 4.76 0.00 0.00Maximum 50.00 50.00 50.00 50.00

Mean 34.01 34.81 31.48 31.67Std. Deviation 5.71 7.09 8.00 7.73

Std. Error of Mean 0.15 0.18 0.21 0.20Margins of Error (95% C.I.) 0.29 0.36 0.40 0.39

Skewness 0.18 0.12 -0.03 -0.09Std. Error of Skewness 0.06 0.06 0.06 0.06

Kurtosis 0.88 0.33 0.36 0.73Std. Error of Kurtosis 0.13 0.13 0.13 0.13

Percentiles 10 27.58 26.19 20.00 20.83 20 30.00 28.57 26.67 25.00 30 31.25 30.95 26.67 29.17 40 32.29 33.33 30.00 29.17 50 33.33 33.33 33.33 33.33 60 34.38 33.33 33.33 33.33 70 36.46 38.10 33.33 33.33 80 38.54 40.48 36.67 37.50 90 41.67 45.24 43.33 41.67


In terms of Disease Prevention, 95% confidence interval of the mean index is between 31.1 and 31.9. The values in the interval all lie within the ‘problematic’ GHL category given that the values lie between the range of 25 and 33.

In terms of Health Promotion, 95% confidence interval for the mean index is between 31.3 and 32.1. The values in the interval all lie within the ‘problematic’ HL category since the values lie between the range of 25 and 33.

Table 11 provides a comparative distribution of the different dimensions of HL at a national level as well as at EU level. One can notice that the mean scores for GHL and Health Care literacy are fairly close whereas the mean values for Disease Prevention and Health Promotion are slightly lower than the EU-HLS scores.

Table 11: Comparative distribution of HLS score

In order to ascertain the validity of these apparent differences, the T-test was computed in Table 12. In this case, this test is assuming that the test variable (index under study) is normally distributed, whilst ignoring the variability in the EU estimates. The Null hypothesis is that the difference between the national indices and those published by the EU is zero.

Table 12: T test on mean GHL scores with EU figures

*This test is assuming that the variables under study are normally distributed and that there is no sampling variability in EU estimates. These assumptions had to be taken since EU-HLS micro data was not available for this test.

GHL Index Health Care Index

Disease Prevention Index

Health Promotion Index

Mean (MT) 34.0 34.8 31.5 31.7

Std. Deviation (MT) 5.7 7.1 8.0 7.7

Mean (EU-HLS) 33.8 34.7 34.2 32.5

Std. Deviation (EU-HLS) 8.0 8.3 8.8 9.1

T – test* Mean (MT) Sig. (2-tailed)

GHL index 34.0 0.161

Health Care Index 34.8 0.546

Disease Prevention Index 31.5 0.000

Health Promotion Index 31.7 0.000


Table 12 shows that the mean GHL index and Health Care index are not statistically different than the EU average values. However, the tests on the Disease Prevention Index and the Health Promotion index proved that the means between the EU and national averages differ significantly. For both, the national Disease Prevention index and the Health Promotion index were significantly lower than the EU average.

3.3 Further examinations

Indices for Malta were further scrutinized by investigating differences in mean indices. Repeated measurements on a single sample were carried out, in order to assess whether their population mean ranks differ. The Wilcoxon Signed-Rank Test, was used to decide whether the corresponding data population distributions were identical without assuming them to follow the normal distribution. The null hypothesis was that the responses of the two indices have identical populations.

Table 13: Wilcoxon Signed rank test for indices

Wilcoxon Signed rank test - p value

Median of differences between Health Care and Health Promotion

0.000

Median of differences between Health Care and Disease Prevention

0.000

Median of differences between Health Promotion and Disease Prevention

0.253

*Wilcoxon Signed Rank Test. Significant at the 0.05 level (2-tailed).

The Wilcoxon Signed rank test p-values provided in table 13, demonstrate that responses for Health care index were statistically significantly different than Health Promotion and Disease Prevention responses, which means that the sample population responses for these two variables were different. However, on comparing Health Promotion and Disease Prevention, the Wilcoxon signed rank test proves that there is no difference in sample responses between the two indices.

“The mean GHL index and Health Care index are not statistically different than the EU average values.”


Table 14: Wilcoxon Signed rank test for indices

Wilcoxon Signed rank test - p value

Median of differences between FHI and UHI 0.000Median of differences between FHI and JHI 0.018

Median of differences between FHI and AHI 0.000Median of differences between UHI and JHI 0.000

Median of differences between UHI and AHI 0.001Median of differences between JHI and AHI 0.000

*Wilcoxon Signed Rank Test. Significant at the 0.05 level (2-tailed).

Similarly, Table 14 confirms that FHI, UHI, JHI and AHI responses differ significantly. At 0.05 significance level, one can conclude that the indices from the dataset have non-identical populations and sample population responses among indices are different.

On the other hand, the Spearman Correlation coefficients in Table 15 indicate that all eight indices are highly correlated between each other. The strongest bivariate correlations involve GHL index which was considered to be the best single measure to represent the sub indices.

Table 15: Spearman Correlation coefficient for HL indices

**Correlation is significant at the 0.01 level (2-tailed).

From the above table one can note that GHL is highly correlated to Health Care and this implies that persons with a high level of GHL tend to have better HL levels for Health Care than the rest of the population. In addition persons with high GHL levels also tend to have high HL levels for UHI given that the correlation between the two aspects is 0.847.

GHL HC DP HP FHI UHI JHI AHI

GHL 1 Health Care 0.809** 1

Disease Prevention

0.714** .413** 1

Health Promotion

0.722** .470** .524** 1

FHI 0.619** .606** .455** .563** 1 UHI 0.847** .683** .682** .708** .422** 1 JHI 0.717** .573** .648** .596** .340** .566** 1 AHI 0.754** .713** .631** .511* .376** .647** .551** 1


4.0 Health Literacy associated with Body Mass Index, self assessed health and long term illness

O ther aspects which are covered in this study concern issues associated with how persons assess their health and whether they suffered from a long term illness, In addition other information concerning weight and height of respondents was collected and subsequently used to calculate the BMI for respondents.

4.1 Body Mass IndexFigure 5 provides the distribution of the population by their Body Mass Index classification (BMI). This was calculated by dividing the weight of respondents by their squared height (kg/m2). This calculation resulted in the highest percentage (38.4%) of the population being estimated to have a ‘normal’ BMI. Those ‘overweight’ made up 35.7%, whilst those categorised as ‘obese’ scored 23.8%. Only 2.1% of respondents were deemed to have an ‘underweight’ BMI. These results were more or less on the same level with those in the EU-HLS. The totals for EU respondents with ‘normal’ BMI were 38.8%, with ‘overweight’ 33.9%, ‘obese’ 25.7% and ‘underweight’ 1.5%.

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%

Underweight Normal Overweight Obese

2.1

38.435.7

23.8

Figure 5: Body Mass Index frequencies


Table 16 provides an overview of the BMI by mean HL components. From the information provided, there do not seem to be statistically significant changes in GHL, Health Care literacy and Disease Prevention literacy among persons with different BMI. On the other hand there are statistically significant differences for Health Promotion literacy levels, with persons with an ‘unknown’ BMI having the lowest indices followed by those classified as ‘obese’. Figures pertaining to ‘underweight’ were not considered since the information is under-represented. Table 16: Distribution of BMI by mean HL level**

*. Independent Sample Kruskal-Wallis Test. Significant at the 0.05 level (2-tailed).**Under-represented values (sample counts of 29 or less) are highlighted in bold font

Table 17: Distribution of BMI by mean HL level and gender*

*Under-represented values (sample counts of 29 or less) are highlighted in bold font

GHL Health Care Disease Prevention

Health Promotion

Underweight 34.78 34.94 33.83 34.49

Normal 34.24 35.14 31.54 32.43*

Overweight 34.35 35.41 32.21 31.84*

Obese 33.50 34.45 31.09 31.10*

Unknown BMI

31.83 32.21 27.89 27.47*

Males GHL Health Care Disease Prevention

Health Promotion

Underweight 36.15 35.31 35.66 38.24

Normal 34.36 35.49 31.64 32.80

Overweight 34.09 35.25 31.94 31.87

Obese 33.67 34.55 30.98 32.11

Unknown BMI 33.46 33.22 28.53 28.32

Females GHL Health Care Disease Prevention

Health Promotion

Underweight 34.78 34.94 33.83 34.49

Normal 34.24 35.14 31.54 32.43

Overweight 34.35 35.41 32.21 31.84

Obese 33.50 34.45 31.09 31.10

Unknown BMI 31.83 32.21 27.89 27.47


0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

%

Table 17 provides the distribution of HL by gender and BMI. There are no statistically significant differences between the literacy levels of males and females. This was determined using the Independent Sample Kruskal-Wallis Test.

4.2 Self-Assessed Health StatusFigure 6 shows the distribution of Self-Assessed Health Status which was measured on a scale of ‘1’ to ‘5’ where ‘1’ was ‘very good’ and ‘5’ was ‘very bad’.

Nearly 60% of the Maltese consider themselves to have good health. On an EU scale this stood at 40%. Persons describing their health to be ‘fair’ made up 21.3% of the total population; at EU level this rate stood at 24.9%.

The mean value of self assessed health status stood at 2.1 whilst the standard deviation was estimated at 0.7. The respective values at EU level were 2.2 and 1.0. The local population therefore reported a slightly better self-assessed health. Furthermore there was a statistically significant difference between persons stating to have ‘very good’ health and ‘bad’ health.

16.8

59.6

21.32.1 0.3

Figure 6: Distribution of Self assessed health

Very Good Good Fair Bad Very Bad

More than one One No long term illness long term illness long term illness

“Nearly 60% of the Maltese consider themselves to have good health.”


Table 18: Distribution of self assessed health by mean HL level**

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.**Under-represented values (sample counts of 29 or less) are highlighted in bold font

When comparing the results of self assessed health with the mean scores for the three different dimensions of HL, one might say that persons who consider themselves to have ‘very good’ health score higher means in terms of their literacy on health care, disease prevention and health promotion. By contrast persons who rate their health to be ‘bad’ have the lowest scores for all dimensions of HL.

4.3 Long term illnesses

Figure 7 Distribution of the population by prevalence of long term illnesses

Self assessed health GHL HC DP HP

Very Good 35.64* 36.79* 32.78* 33.82*

Good 33.98* 34.78* 31.62* 31.77*

Fair 33.05* 33.71* 30.28* 29.95*

Bad 31.08* 30.41* 30.04* 29.73*

Very bad 32.64 35.64 22.43 19.71

Don’t know 33.25 30.90 28.32 35.43

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

%

More than one One No long term illness long term illness long term illness

8.527.4

64.2


Nearly two thirds of the population is estimated not to have long term illnesses or health problems. This was more or less the same on EU-HLS level with 65% of interviewees stating not to suffer from any long term illness or health issue.

Table 19: Distribution of long term illness frequency by General Health Literacy level

Table 19 provides the mean HL level by gender and frequency of long term illness. Using the Independent Sample Kruskal-Wallis test, no statistically significant difference in HL levels was determined among persons suffering from long term illness.

Figure 8 Limitations of activities from health problems

Persons who suffer from long term illnesses were asked to provide feedback on whether the health problem limited the activities they carry out on a regular basis. An estimated 20.6% were ‘severely limited’ in their usual activities as a result of their long term illness. A further 40.8% were limited to a certain extent whereas 38.5% did not have any limitations.

Severely Limited but not severely Not limited at all

Long term illness Males Females Total

More than one illness 33.90 32.64 33.14

One illness 33.79 33.88 33.84

No illness 34.17 34.18 34.18

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%

20.6

40.8 38.5


5.0 The Importance of the Social Gradient for Self-Perceived Health

T he national HLS included a number of questions to explore and determine whether HL levels of respondents and financial deprivation are linked. This was done through the use of three different questions, namely, whether respondent was able to pay for medication to manage own health, if respondent afforded to pay for a visit to the doctor and whether respondent was in a position to pay bills at the end of the month. In addition, information on the net monthly household income was provided to assess the household’s economic standing.

Table 20: Distribution of population by financial deprivation elements*


From Table 20 an estimated, 53.6% of the population have no difficulties to pay for medication if needed. In assessing the information provided for this question one must take into account that respondents were specifically asked to consider to have to pay for any medication (irrespective of price), despite the fact that they may have been entitled to have it for free. The majority of the population found it fairly easy to pay for a visit to the doctor, whereas 54.5% declared that they have no difficulty in paying for bills.

Category Percentage distribution

Ability to pay for medication if needed

Very easy 3.0%

Fairly easy 50.6%

Fairly difficult 43.8%

Very difficult 2.6%

Ability to pay for a visit at the doctor

Very easy 6.0%

Fairly easy 60.5%

Fairly difficult 32.2%

Very difficult 1.3%

Difficulty to pay bills

Almost no difficulty ever 54.5%

Difficulty from time to time

32.4%

Difficulty most of the time 13.1%


When looking at the distribution of the net household income, one notes that 46.1% of respondents had a net monthly income under €1,350. It is important to note however that 17.3% of respondents did not answer to this question.

Table 21: Distribution of population by net monthly household income

Additional information on mean GHL levels is provided in Table 22. The highest mean HL scores were obtained by persons who found it ‘very easy’ to pay for medication should it be required. This category of persons scored significantly higher means in all the other dimensions of HL when compared to the other sub-groups for this variable. High HL levels were also recorded among persons who found it ‘very easy’ to afford to pay for a visit to the doctor. Once more this category had by large better HL scores in all HL dimensions when compared to the other sub-groups for this variable. When considering household income, those with a higher net income resulted to have better HL scores than the rest of the other categories.

On the other hand, persons who had the most difficulties in paying monthly bills (13% of respondents) had the highest levels of literacy for the three dimensions of HL. Given the trends established by the other three financial parameters exhibiting significant links between financial deprivation and lower levels of HL, the difficulty to pay monthly bills as an indicator of financial deprivation merits discussion.

Net household income per month Percentage distribution

Less than €800 24.4%

€800 to under €1350 21.8%

€1350 to under €1850 11.9%

€1850 to under €2400 10.6%

€2400 to under €2950 5.8%

€2950 to under €3600 4.1%

€3600 and over 4.1%

Don’t know/ Refusal 17.3%

“High HL levels were recorded among persons who found it ‘very easy’ to afford to pay for a visit to the doctor.”


* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at 5% confidence level.**Under-represented values (sample counts of 29 or less) are highlighted in bold font

Category GHL HC DP HP

Ability to pay for medication if needed

Very easy 40.09* 41.61* 37.42* 37.45*

Fairly easy 33.71* 34.25* 31.28* 31.80*

Fairly difficult 33.79* 34.85* 31.36* 31.22*

Very difficult 34.05* 35.68* 30.66* 29.86*

Ability to pay for a visit at the doctor

Very easy 35.79* 37.05* 33.66* 33.48*

Fairly easy 34.09* 34.88* 31.59* 31.98*

Fairly difficult 33.54* 34.42* 30.98* 30.75*

Very difficult 34.37 35.05 31.82 32.96

Difficulty to pay bills

Almost no difficulty ever

33.50* 34.08* 30.63* 30.92*

Difficulty from time to time

34.53* 35.61* 32.45* 32.22*

Difficulty most of the time

34.43* 35.02* 33.54* 32.81*

Net household income

Less than €800 34.09* 35.20* 31.21 31.81*

€800 to under €1350

33.79* 34.34* 31.74 31.49*

€1350 to under €1850

34.09* 35.10* 32.08 31.56*

€1850 to under €2400

34.11* 35.43* 31.64 32.21*

€2400 to under €2950

33.03* 34.28* 31.28 31.14*

€2950 to under €3600

34.72* 35.83* 32.87 32.62*

€3600 and over 36.73* 37.96* 33.74 34.80*

Don’t know/ Refusal

33.49* 33.38* 30.13 30.56*

Table 22: Mean HL levels for financial deprivation elements and household net income**


Table 23 provides the link between the net household income and the difficulty faced by persons in paying for their monthly bills. One can note that out of all persons who had the most difficulty in paying monthly bills, 33.4% stated to have monthly net household income of less than €800 and hence one can deduce that there is a link between the income of the household and the ability to pay bills.

Table 23: Distribution of income by difficulty to pay bills

Difficulty to pay monthly bills (%)

Net household

income

Almost neverFrom time to

timeMost of the

time

Less than €800 22.63 38.78 33.42€800 to under

€135024.09 30.83 28.51

€1350 to under €1850

17.05 12.10 12.88

€1850 to under €2400

15.57 10.21 7.03

€2400 to under €2950

8.30 5.10 8.91

€2950 to under €3600

6.58 1.49 5.69

€3600 and over

5.79 1.49 3.57

Total 100 100 100


6.0 Proportions of Limited Health Literacy in Vulnerable Populations

T he outcome from the HLS conveys that some subpopulations of vulnerable groups experience limited general HL. In this regard, individuals with limited general HL levels fell into the ‘inadequate’ or ‘problematic’ GHL categories.

Very vulnerable groups are identified by subgroups who have 60% of individuals with limited HL. In the national survey the indicators where the very vulnerable groups were identified were those subpopulations with persons with ‘very low’ self assessed social status (60.6%) and ‘bad’ self-perceived health (61.6%) as Table 22 indicates.

Table 24: Percentage of persons with limited HL in very vulnerable groups*


The EU-HLS Study identified a much larger number of very vulnerable population subgroups. Table 25 illustrates a comparative analysis between the EU-HLS and the national survey for the very vulnerable population subgroups. The information from the European study indicates that the very vulnerable groups for the average EU total were made up of persons who were 76 years or older; with a very low social status; a bad to very bad self assessed health; and low education. Persons who were not in a position to pay for medication and to visit a doctor and who experienced severe health related problems were also part of the very vulnerable category.

Indicator Category % with limited GHL

Social Status Very Low 60.6

Self-perceived health Bad 61.6


Table 25: Comparative analysis in the percentage of individuals with limited GHL in very vulnerable groups*

*Under-represented values (sample counts of 29 or less) are highlighted in bold font1ISCED 1997 is an international classification on education made up of 6 levels – ISCED 0 – Pre primary education; ISCED 1 – Primary education; ISCED 2 – Lower secondary education; ISCED 3 – Upper secondary education; ISCED 4 – Post secondary non tertiary; ISCED 5 – First stage of tertiary education; ISCED 6 – Second stage of tertiary education

Compared to the EU total, the national results for very vulnerable groups show relatively smaller shares of individuals with limited HL for all indicators.

Vulnerable groups are identified as population subgroups who have more than 50% and less than 60% of individuals with limited HL. Table 26 gives the percentages for vulnerable groups within the Maltese population. The vulnerable category includes persons aged 76 years or more; persons residing in Gozo and Comino; and persons with more than one long term illness.

Indicator Category % with limited GHL

Malta EU Total

Social Status Very Low 60.6 73.9

Self-perceived health Bad; Very Bad 60.4 72.8

Education (ISCED Level)(1) Level 0, Level 1 48.9 68

Able to pay for medication Very difficult 50.3 67.1

Able to afford doctorFairly difficult, very

difficult48.3 66.5

Limited activities by health problems

Severely limited 50.8 65.6

Monthly household income Less than €800 44.1 65.6

Able to pay for medication Fairly difficult 46.3 63.6

Difficulties paying bills Most of the time 38.1 63.4

Long term illness Yes more than one 56.3 61

Age 76 or older 54.4 60.8

Social Status Low 46.5 60

“The national results for very vulnerable groups show relatively smaller shares of individuals with limited HL for all indicators.”


Table 26: Percentage of individuals with limited GHL in vulnerable groups*


Table 27 provides a comparative analysis of indicators which were identified in the EU-HLS Study as vulnerable subpopulations. The national level for the same indicator and category is provided for comparative analysis.

When comparing to the EU-HLS findings, Malta scores better for all of these subgroups except for persons with lower middle social status, which implies, that the same subgroups at a national level have a better HL level than those persons interviewed in the EU-HLS.

INDICATOR CATEGORY PROPORTION with limited GHL (%)

Self-perceived health Fair 55.8

Self-associated social status Low middle 53.6

Able to pay for medication Very difficult 50.3

Long term illness Yes more than one 56.3

Age 76 and over 54.4

Marital status Widowed 51.1

Number of emergency service contacts (last 24 months)

1-2 times 51.0

District Gozo and Comino 56.1

Service use from other health professionals

0 times 50.0

Limited activities by health problems Severely limited 50.8


Table 27: Comparative analysis of individuals with limited GHL in vulnerable groups*


INDICATOR CATEGORYPROPORTIONwith limited GHL (%)

Malta EU-HLSSelf-perceived health Fair 55.8 59.4

Marital status Widowed 51.1 59.1Number of doctor visits (last 12

month)6 times or more 48.4 58.8

Limited activities by health problems Limited but not severely 49.1 58.2Age Between 66 and 75 43.5 58.1

Main status of employment In retirement or early retirement 45.8 57.8Monthly household income €800 to under €1,350 45.8 57.7

Education (ISCED Level) Level 2 44.1 57.2Main status of employment Unemployed 24.9 55.4

Long term illness Yes one 47.9 55.2Able to afford doctor Fairly easy 45.0 54.2

Difficulties paying bills From time to time 44.2 53.2Number of emergency service

contacts (last 24 months)3 times or more 48.3 53.2

Social Status Lower middle 53.6 53.1Number of hospital stays (last 12

month)3 times or more 47.7 53.0

Monthly household income €1,350 to under €1,850 45. 2 52.1Number of visits to other health

professionals (last 12 month)0 50.0 51.9

Number of emergency service contacts (last 24 month)

1-2 times 51.0 51.4

Number of hospital stays (last 12 month)

1-2 times 47.8 50.7

Body Mass Index Group Overweight 43.2 50.2Active community Involvement Not at all 44.9 50.1

Age between 56 and 65 43.5 50.1


7.0 Health Service Use: Emergency Services, Hospitals, Doctors and Other Health Professionals – Percentages and Associations

H ealth service use is generated by four measures, namely, frequency of contacts with emergency services in the last 2 years, hospital admissions, doctor visits and use of services from other health professionals in the previous 12 months.

7.1 Emergency Services

From Figure 9, 20.7% of respondents had contacted emergency services 1 to 2 times during the course of the previous two years, whereas 3.1% used the emergency services three or more times. The majority, or 76.3%, had not used emergency services at all.

Figure 9: Emergency services frequencies

Table 28 provides information on the HL level of persons by frequency of use of emergency services. Using the Kruskal-Wallis test, there were no statistically significant differences between the literacy levels of persons and the frequency of use of emergency services.

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0%

No use of 1 - 2 3 - 5 6 or moreemergency services

76.3

20.72.4 0.7


Table 28: GHL index by frequency of emergency service useEmergency service use Male Female TotalNo use of emergency services 34.08 33.99 34.03

1 to 2 times 33.94 33.85 33.903 or more times 33.25 32.92 33.09

Further information on the different dimensions of HL is presented in Table 29. Despite the apparent differences between the different dimensions of GHL, using the Kruskal-Wallace test of differences in distributions, it is apparent that the differences in indices’ distributions are unaffected by frequency of emergency service use.

Table 29: Distribution of persons by frequency of emergency service use and dimensions of HL

Emergency service use GHL HC DP HP

No use of emergency services 34.03 34.92 31.54 31.74

1 to 2 times 33.90 34.61 31.17 31.453 or more times 33.09 32.70 30.92 30.33

* Null hypothesis for Independent Sample Kruskal-Wallis test accepted at the 5% confidence level.

7.2 Hospital Service Use

Figure 10 illustrates that the majority of the population never used hospital services in the previous year, while 28.6% used hospital services 1 to 2 times in the previous year. A relatively smaller percentage (9.2%) stated a frequency of 3 to 5 times and a further 4.9% used hospital services 6 or more times.

0.0

10.0

20.0

30.0

40.0

50.0

60.0%

No use of 1 - 2 3 - 5 6 or morehospital service

57.2

28.6

9.2 4.9

Figure 10: Hospital service frequencies


Table 30 provides the indices of HL for general health and the three different dimensions of health, namely, health care, disease prevention and health promotion. Using the Kruskal-Wallis test, there result to be no statistically significant difference between persons who use hospital services and those who do not.

Table 30: Distribution of persons by frequency of hospital service use and dimensions of HL

* Null hypothesis for Independent Sample Kruskal-Wallis test accepted at the 5% confidence level.

7.3 Doctor Visits

The national survey included information on the frequency of doctor visits in the previous twelve months. As Figure 11 illustrates the majority of the population is estimated to have visited a doctor between one to five times in the previous year. This is in contrast with the use of hospital health services.

Figure 11: Doctor visits frequencies

Hospital service use GHL HC DP HP

No use of hospital services 34.12 35.13 31.39 31.751 to 2 times 33.84 34.46 31.73 31.713 to 5 times 33.44 34.00 31.26 30.81

6 times or more 34.15 34.42 30.72 31.44

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0%

No visits 1 - 2 3 - 5 6 or more

39.0

30.3

16.7

14.0


Table 31: Distribution of persons by frequency of doctor visits and dimensions of HL

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at the 5% confidence level.

Table 31 provides the distribution of persons by frequency of doctor visits and dimensions of HL. Persons who never had doctor visits in the previous year, in general, resulted to be more health care literate than the rest of the population who made use of a doctor at any point during the same period. In all instances, better literacy levels of health care were present across all the population irrespective of the frequency of doctor visits.

7.4 Other health professional services

In relation to doctor visits, the service of other health professionals tended to be less popular among respondents. Just under 67% of the population is estimated to have made use of services provided by other health professionals as Figure 12 illustrates.

Frequency of doctor visits GHL HC DP HP

No doctor visits 34.12 35.13* 31.39 31.751 to 2 times 33.84 34.46* 31.73 31.713 to 5 times 33.44 34.00* 31.26 30.81

6 times or more 34.15 34.42* 30.72 31.44

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

55.0%

No visits 1 - 2 3 - 5 6 or more

33.0

51.1

11.44.5

Figure 12: Other health professional visits frequencies


Table 32: Distribution of persons by frequency of other health professional visits and dimensions of HL

* Null hypothesis for Independent Sample Kruskal-Wallis test rejected at the 5% confidence level.

In contrast to findings for other health-related services, persons who made use of other health professional services 1 to 2 times in the previous year, were significantly more health literate than the rest of the other subgroups for all dimensions of HL.

Table 33 provides a number of cross correlations between the different indicators for health service use. The cross correlations between the four kinds of services are all significant and positive. The strongest correlation is exhibited between doctor visits and hospital services (0.333). The second strongest bivariate association is recorded between emergency service use and hospital services (0.328).

Table 33: Cross Correlations between Indicators for Health Service Use

Frequency of other health professional visits GHL HC DP HP

No other health professional visits

33.44* 34.05* 30.37* 31.03*

1 to 2 times 34.43* 35.47* 32.28* 32.26*3 to 5 times 33.79* 34.49* 31.69* 30.85*

6 times or more 33.85* 33.84* 30.08* 31.79*

Emergency service

Doctor visits

Hospital Service

Other health professionals

Emergency service Corr. Coeff 1.000

Doctorvisits Corr. Coeff 0.154 1.000

Hospital service Corr. Coeff 0.328 0.333 1.000

Other Health Professionals Corr. Coeff 0.078 0.179 0.185 1.000


8.0 Conclusion

T he HLS conducted during July 2014, concluded that 45.0% of the population who is over 18 years old has a ‘sufficient’ level of HL. Just about the same amount (42.5%) of the population resulted to have a ‘problematic’ level of HL. The mean HL Index recorded was of 34.0 and this compares quite well with the findings of the EU-HLS Study European General HL Index of 33.8. No statistically significant differences were identified among different age groups, gender, persons of different marital status or persons residing in different districts. In addition, statistical tests also concluded that there were no significant differences among different types of households, households with or without children or persons with a different self assessed social status. Persons with a tertiary level of education were found to be more health literate than the other educational attainment subgroups of the population.

Individuals who considered their health to be ‘very good’ had better HL than the rest of the population subgroup. In addition, those persons who found no problems in paying for medication should it have been necessary or who could afford to pay for doctor visits, tended to have better HL levels.

In terms of very vulnerable or vulnerable groups, defined as population subgroups having more than 50% of individuals with limited HL, a number of sub-populations were identified at a national level. These included persons with very low or lower middle self-assessed social status; persons with ‘bad’ or ‘fair’ self-perceived health; persons with two or more long term illnesses; individuals who stated they were severely limited by their health problems; residents of Gozo and Comino; persons aged 76 years and over; widows; persons who used emergency services between 1-2 times in the previous 24 months; and persons who found it very difficult to pay for medication should it have been necessary.

The above are only the main findings of this survey. Further analysis of the information collected in this study is bound to produce more interesting findings which can shed light on the national situation when it comes to HL and associated issues. We therefore believe that this report should be viewed as just the start of this work and that further analysis will produce interesting results that can influence the direction of future policy in this area.


ANNEX 1HLS-EU - Q16 - MALTI

Fuq skala minn faċli ħafna għal diffiċli ħafna, kemm taħseb li jkun faċli li:

Faċli ħafna

Faċli DiffiċliDiffiċli ħafna

1 …ssib informazzjoni dwar kura jew trattament għall-mard li jkollok? 1 2 3 4

2 …ssir taf fejn għandek tfittex għajnuna professjonali f ’każ ta’ mard? (Instructions: such as doctor, pharmacist, psychologist) 1 2 3 4

3 …tifhem x’jgħidlek it-tabib? 1 2 3 4

4 …tifhem l-istruzzjonijiet tat-tabib jew l-ispiżjar tiegħek dwar kif għandek tieħu l-mediċina li jkun kitiblek it tabib? 1 2 3 4

5 …tagħraf meta jkollok bżonn tieħu opinjoni oħra mingħand tabib ieħor? 1 2 3 4

6 …tagħmel użu mill-informazzjoni li jagħtik it-tabib biex tieħu d-deċiżjonijiet dwar il-mard tiegħek? 1 2 3 4

7 …ssegwi l-istruzzjonijiet tat-tabib jew l-ispiżjar tiegħek? 1 2 3 4

8 …ssib informazzjoni dwar kif tikkontrolla problemi ta’ saħħa mentali bħal stress jew dipressjoni? 1 2 3 4

9 …tifhem twissijiet għas-saħħa marbuta ma’ mgieba bhal tipjip, nuqqas ta’ attività fiżika u xorb żejjed? 1 2 3 4

10 …tifhem għalfejn għandek bżonn tagħmel ‘screening’ ghal xi mard? (Instructions: breast exam, blood sugar test, blood pressure) 1 2 3 4

11…tagħraf jekk l-informazzjoni dwar ir-riskji għas-saħħa li tingħata fuq

il-mezzi tax-xandir tkunx tista’ toqgħod fuqha? (Instructions: TV, Internet or other media)

1 2 3 4

12…tiddeċiedi kif tista’ tħares lilek innifsek mill-mard skont

l-informazzjoni li tingħata fuq il-mezzi tax-xandir? (Instructions: Newspapers, leaflets, Internet or other media?)

1 2 3 4

13 …ssir taf dwar attivitajiet li huma ta’ ġid għas-saħħa mentali tiegħek? (Instructions: meditation, exercise, walking, pilates etc.) 1 2 3 4

14 …tifhem pariri dwar is-saħħa mingħand membri tal-familja jew mill-ħbieb? 1 2 3 4

15…tifhem informazzjoni dwar kif ittejjeb saħħtek li tingħata minn fuq

il-mezzi tax-xandir? (Instructions: Internet, newspapers,magazines)

1 2 3 4

16 …tagħraf liema mġieba ta’ kuljum taffettwalek saħħtek? (Instructions: Drinking and eating habits, exercise etc.) 1 2 3 4


ANNEX 2HLS-EU - Q16 - ENGLISH

On a scale from very easy to very difficult, how easy would you say it is to:Very easy

Fairly easy

Fairly difficult

Very difficult

Don’t Know (Spontane-

ous)

1 …find information on treatments of illnesses that concern you? 1 2 3 4 5

2…find out where to get professional help when you are ill?

(Instructions: such as doctor, pharmacist, psychologist)1 2 3 4 5

3 …understand what your doctor says to you? 1 2 3 4 5

4…understand your doctor’s or pharmacist’s instruction on how

to take a prescribed medicine?1 2 3 4 5

5…judge when you may need to get a second opinion from

another doctor?1 2 3 4 5

6…use information the doctor gives you to make decisions

about your illness?1 2 3 4 5

7 …follow instructions from your doctor or pharmacist? 1 2 3 4 5

8…find information on how to manage mental health problems

like stress or depression?1 2 3 4 5

9…understand health warnings about behaviour such as smoking, low physical activity and drinking too much?

1 2 3 4 5

10…understand why you need health screenings?

(Instructions: breast exam, blood sugar test, blood pressure)1 2 3 4 5

11…judge if the information on health risks in the media is

reliable? (Instructions: TV, Internet or other media)1 2 3 4 5

12…decide how you can protect yourself from illness based on

information in the media? (Instructions: Newspapers, leaflets, Internet or other media?)

1 2 3 4 5

13…find out about activities that are good for your mental well-being? (Instructions: meditation, exercise, walking, pilates etc.)

1 2 3 4 5

14 …understand advice on health from family members or friends? 1 2 3 4 5

15…understand information in the media on how to get

healthier? (Instructions: Internet, newspapers,magazines)1 2 3 4 5




Published by the Office of the Commissioner for Mental HealthSt Luke’s Square, G’Mangia, PTA 1010

Electronic version available fromWebsite:

http://health.gov.mt/en/CommMentalHealth/Pages/Commissioner-For-Mental-Health.aspx

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