- .QUESTION Identifying and Interpreting Statistics in Research Articles
STAT6000_Assessment Brief 2 Page 1 of 3
ASSESSMENT BRIEF Subject Code and Title STAT6000: Statistics for Public Health Assessment Assessment 2: Assignment – Identifying and Interpreting Statistics in Research Articles Individual/Group Individual Length 2000 Learning Outcomes This assessment addresses the following learning outcomes:
1. Understand key concepts in statistics and the way in which both descriptive and inferential statistics are used to measure, describe and predict health and illness and the effects of interventions.
5. Apply key terms and concepts of statistics, including; sampling, hypothesis testing, validity and reliability, statistical significance and effect size.
6. Interpret the results of commonly used statistical tests presented in published literature.
Submission Due Sunday following the end of Module 4 at 11:55pm AEST/AEDT* Weighting 30% Total Marks 100 marks ORIGINAL ARTICLE
The rising tide of diabetes mellitus in a Chinese population:
a population-based household survey on 121,895 persons
Martin C. S. Wong • Michael C. M. Leung •
Caroline S. H. Tsang • S. V. Lo • Sian M. Griffiths
Received: 27 June 2011 / Revised: 14 April 2012 / Accepted: 16 April 2012 / Published online: 3 May 2012
_ Swiss School of Public Health 2012
Abstract
Objectives We studied the prevalence of self-reported
diabetes mellitus in selected years from 2001 to 2008, and
evaluated the factors associated with diabetes.
Methods From territory-wide household interviews in a
Chinese population in the years 2001, 2002, 2005 and
2008, we evaluated the trend of self-reported diabetes with
respect to age, sex and household income. Binary logistic
regression analyses were conducted to study the independent
factors associated with diabetes.
Results From 121,895 respondents in the household surveys,
103,367 were adults aged 15 years or older. Among
male respondents, the age- and sex-adjusted prevalence of
diabetes in 2001, 2002, 2005 and 2008 was 2.80, 2.87, 3.32
and 4.66 %, respectively; while among female respondents
the respective prevalence was 3.25, 3.37, 3.77 and 4.31 %.
In all the years, the prevalence escalated with age and
increased sharply among the poor. From binary logistic
regression analyses, advanced age and low monthly
household income were significantly associated with selfreport
of diabetes.
Conclusions This study showed a rising trend of diabetes
mellitus in a large Chinese population and found a strong
association between population demography and diabetes.
Keywords Diabetes mellitus _ Prevalence _ Age _
Gender _ Socioeconomic status
Introduction
Diabetes mellitus imposes a substantial burden to the
healthcare system and is recognized as a worldwide health
crisis (Feinglos and Bethel 2007). There is an estimated
20.8 million people affected in the US in 2002, and the
costs incurred amount to $132 billion (Hogan et al. 2003).
The World Health Organization estimates for the number
of persons affected by diabetes were 171 millions in 2000
and 266 millions in 2030 (Wild et al. 2004), while the
International Diabetes Federation estimates were 246 millions
in 2007 and 380 millions in 2025 (International
Diabetes Federation 2006). A significant increase in the
number of people affected by diabetes is expected in the
next few decades.
Varying prevalence rates of diabetes were reported in
different countries. According to the National Health and
Nutrition Examination Survey (NHANES), the prevalence
of diabetes was 9.3 % among adults aged 20 years or older
(Cowie et al. 2006). In the UK, the prevalence of type 2
diabetes was 3.2 and 4.7 % in Europoid men and women,
respectively; while among Asians living in the same city of
Coventry, the respective figures were 12.4 and 11.2 %
(Simmons et al. 1991). It was found that the higher prevalence
of diabetes in Asians than the Europoids were not
attributable to obesity, implying that a lesser extent of
excess of adiposity is required in Asians than in Europoids
for the development of diabetes. Ethnicity therefore plays
an important role in precipitating diabetes.
The International Collaborative Study of Cardiovascular
Disease in Asia conducted in 2000–2001 found that the
- C. S. Wong (&) _ M. C. M. Leung _ S. M. Griffiths
School of Public Health and Primary Care, Faculty of Medicine,
Chinese University of Hong Kong, 4/F, School of Public Health
and Primary Care, Prince of Wales Hospital, Shatin, NT,
Hong Kong SAR, China
e-mail: [email protected]
- S. H. Tsang _ S. V. Lo
Food and Health Bureau, The Government of the Hong Kong
Special Administrative Region, Hong Kong SAR, China
Int J Public Health (2013) 58:269–276
DOI 10.1007/s00038-012-0364-y
123
prevalence of self-reported diabetes was 1.3 % (Gu et al.
2003), and the age-standardized true prevalence of diabetes
was higher in subjects living in northern compared to
southern China (7.4 vs. 5.4 %, p\0.001). In addition,
those living in urban areas had higher prevalence than
residents in rural areas (7.8 vs. 5.1 %, p\0.001). Hong
Kong is one of the most rapidly developing economies in
Asia (Leung et al. 2005); its westernization, urbanization
and cultural mix due to population mobility could contribute
to a higher diabetes prevalence. Previous studies in
Hong Kong showed that the prevalence ranged from 2 % in
people aged\35 years to 20 % in those 65 years or older
(Chan et al. 2009; Department of Health, The Government
of Hong Kong Special Administrative Region 2012; Janus
et al. 2000). The incidence of diabetes is increasing in
Hong Kong, but more than half of those affected remain
undiagnosed (Janus et al. 2000; Wong and Wang 2006). By
2025, it was estimated that 12.8 % of the Hong Kong
population, or 1 million people, will suffer from diabetes
(Diabetes Hong Kong 2008). However, there is a scarcity
of large-scale studies which adopted a representative
sampling methodology in recent years to inform public
health policy.
The objectives of this study are to evaluate the prevalence
of self-reported diabetes by territory-wide household
surveys representative of the whole Hong Kong population,
and examined the factors independently associated with
diabetes.
Methods
Sampling frame and methodology
The detailed methodology has been described elsewhere
(Leung et al. 2005; Census and Statistics Department
2010). The Census and Statistics Department, the Government
of the Hong Kong Special Administrative Region
commissioned Thematic Household Surveys (THS) on
health-related issues in 2001, 2002, 2005 and 2008. A
major objective of these surveys was to collect information
on the health status of the Hong Kong population. The
household surveys included all the land-based population
of Hong Kong who were residents in non-institutional
settings. They excluded hotel transients, persons residing
on board vessels and foreign live-in domestic helpers. The
survey field works in 2001, 2002, 2005 and 2008 were
conducted in the time periods Jan 2001–May 2001; May
2002–July 2002; Nov 2005–Mar 2006 and Feb 2008–May
2008, respectively.
Based on a sample of quarters selected from all permanent
quarters and quarters in segments which are for
residential and partially residential purposes in Hong Kong,
these household surveys were conducted in accordance
with a scientifically designed sampling scheme. The present
study adopted a stratified random sampling methodology.
The sampling units included permanent quarters
in built-up regions and segments in non-built-up regions.
The Register of Quarters consists of computerized records
of all addresses of permanent quarters in built-up regions.
These regions included urban areas, new towns and other
major developed areas. Unique address was used to identify
each unit of quarters with information like street name,
building name, floor and flat number. The Register of
Segments consists of records of segments in non-built-up
areas, identified by relatively permanent and delineated
landmarks like footpaths and rivers. The household surveys
covered approximately 96 % of the total Hong Kong resident
population. The approximate response rates for these
household surveys were 75 %, consistently across all four
survey rounds.
Interviewers and survey instrument
The design of the surveys obtained input from the Hong
Kong Government. A Research firms commissioned by the
Census and Statistics Department of Hong Kong trained all
interviewers using a standardized method for face-to-face
interviews. The survey question related to the outcome
variable was ‘‘Do you have any disease that require longterm
follow-up by doctors?’’ in 2001; the wordings of the
corresponding questions in the other two rounds are
slightly different; specifically, ‘‘Have you ever been diagnosed
by a doctor to suffer from the following chronic/
long-term diseases?’’ in 2002; and ‘‘Do you have the following
chronic or long-term disease(s) diagnosed by a
medical doctor, which require long-term follow-up?’’ in
- The corresponding question in 2008 was ‘‘Have you
ever been told by a western medicine practitioner that you
had the following chronic health conditions?’’ If the
respondents gave a positive reply, they were further asked
whether they had diabetes. The interviewers also recorded
demographic information such as age, sex and monthly
household income.
Outcome variables and statistical analysis
STATA version 8.0 was used for all data analysis. The
primary outcome variable was rates of self-reported diabetes
mellitus, defined as a positive reply to the abovementioned
questions. We studied the proportion of survey
respondents having diabetes in 2001, 2002, 2005 and 2008,
and compared the trends according to age, sex and income
as a proxy measure of socioeconomic status. We used ageand
sex-adjusted prevalence rates taking into account
changes in population demography across the years. A
270 M. C. S. Wong et al.
123
binary logistic regression model was conducted with selfreported
diabetes as the outcome variable. Age (referent
0–39 years), sex (referent female) and monthly household
income (referent C $50,000) were used as covariates in the
regression analysis. To explore any heterogeneity in association
between increasing age- and self-reported diabetes
among men versus women, we stratified all subjects
according to sex and similar regression analyses were run
separately for male and female groups. P values B0.05
were regarded as statistically significant.
Results
A total of 33,609, 29,561, 29,802 and 28,923 interviews
were successfully conducted in the years 2001, 2002, 2005
and 2008, respectively. Among them, 103,367 were adults
aged 15 years or above. Their average age was 38.2 years.
Table 1 illustrated the distribution of age, sex and monthly
household income of the respondents. In general, the
respondents were older and had higher monthly household
income in surveys conducted in more recent years (both
p\0.001) (Table 1). The characteristics of respondents
were different which implied a change in population
structure since the sample methodology was similar across
the years. The age-adjusted prevalence of diabetes among
male adults was 2.80, 2.87, 3.32 and 4.66 % in years 2001,
2002, 2005 and 2008, respectively. Among female adults,
the respective prevalence was 3.25, 3.37, 3.77 and 4.31 %
(sex-specific logistic regression models, all p\0.001)
(Fig. 1; Tables 2, 3). The adjusted prevalence in both sex
groups showed a drastic rise with increasing age. There
was a progressive rising trend of self-reported diabetes
across the years 2001–2008 in the age groups C75 years.
From logistic regression analysis using year 2001 as a
reference controlling for age, the relative rates of increase
Table 1 Respondent characteristics (N = 121,895) in the household face-to-face interviews conducted in Hong Kong, China by stratified
random sampling of living quarters in the whole territory in the years 2001, 2002, 2005 and 2008
All 2001 (n = 33,609) 2002 (n = 29,561) 2005 (n = 29,802) 2008 (n = 28,923)
No. % No. % No. % No. %. No. %
Age (years)
\15 18,528 15.2 5,683 16.9 4,951 16.7 4,179 14.0 3,715 12.8
15–24 16,834 13.8 4,808 14.3 3,945 13.3 4,138 13.9 3,943 13.6
25–34 17,751 14.6 5,418 16.1 4,290 14.5 4,174 14.0 3,869 13.4
35–44 22,206 18.2 6,472 19.3 5,703 19.3 5,286 17.7 4,745 16.4
45–54 20,033 16.4 4,856 14.4 4,506 15.2 5,346 17.9 5,325 18.4
55–64 11,179 9.2 2,493 7.4 2,463 8.3 2,939 9.9 3,284 11.4
65–74 9,139 7.5 2,522 7.5 2,225 7.5 2,165 7.3 2,227 7.7
C75 6,225 5.1 1,357 4.0 1,478 5.0 1,575 5.3 1,815 6.3
Sex
Male 60,064 49.8 16,484 49.0 14,663 49.6 14,728 49.4 14,189 49.1
Female 61,831 50.2 17,125 51.0 14,898 50.4 15,074 50.6 14,734 50.9
Monthly household income (HK dollars)a
C50,000 12,452 10.4 4,128 12.3 2,512 9.0 2,357 8.1 3,455 11.9
25,000–49,999 32,748 27.4 9,624 28.6 6,823 24.6 8,415 28.9 7,886 27.3
10,000–24,999 50,648 42.4 13,695 40.7 11,927 43.0 13,153 45.2 11,873 41.1
B9,999 23,578 19.7 6,162 18.3 6,502 23.4 5,205 17.9 5,709 19.7
a There are 2,469 observations with missing information of household income. It shows the demographic characteristics of all survey
respondents
Fig. 1 The prevalence of self-reported diabetes among persons aged
C15 years in selected years from 2001 to 2008 in the household faceto-
face interviews conducted in Hong Kong, China in the years 2001,
2002, 2005 and 2008 by stratified random sampling of living quarters
in the whole territory. The prevalence is age-adjusted across different
years
Rising tide of diabetes mellitus in a Chinese population 271
123
in prevalence among male adults (27.8 and 47.9 % in 2005
and 2008, respectively) were lower than those among
female adults (31.8 and 69.3 %, respectively) (p\0.001).
The age- and sex-adjusted (‘‘population adjusted’’ thereafter)
prevalence progressively increased across the years
in the two lowest income groups among male and female
respondents. There was however no definite observed differences
in prevalence trends between male and female
respondents (Table 4).
When the independent association between patient
demographics and rates of diabetes was analyzed by multivariate
regression models, older age [adjusted odds ratio
(AOR) 32.2, 95% CI 20.6–50.4, p\0.001 for 40–65 years;
AOR 120.1, 95% CI 76.6–188.3, p\0.001 for older than
65 years) and lower income (AOR 2.19, 95% CI 1.66–2.88,
p\0.001 for monthly household income BHK$9,999 or
US$1,287) were significantly associated with diabetes
(Table 5). The respondents’ sex has no association with the
prevalence of diabetes. There exists a trend that the association
between advanced age and diabetes was more
marked among male respondents (AOR 45.4, 95% CI
22.5–91.8 for age 40–65 years; AOR141.1 95% CI
69.5–286.5 for age older than 65 years; both p\0.001)
when compared with female respondents (AOR 23.5, 95%
CI 13.1–42.0 for age 40–65 years; AOR 105.5, 95% CI
58.9–188.8 for age older than 65 years; both p\0.001)
(Table 5). There exists no multicollinearity in the regression
analysis. The coefficient of determination (R2), defined
as the proportion of variability in a dataset that is
accounted for by the statistical model (Steel and Torrie
1960), was 0.198. It indicated that the independent variables
entered into this regression analysis accounted for
19.8 % of the variability of diabetes prevalence.
Discussion
Major findings
Our study found that the prevalence of self-reported diabetes
increased by approximately 50 % from 2001 to 2008,
and the rise was especially drastic among female residents
(69.3 %) when compared with male respondents (47.9 %).
Besides, we did not detect any significant differences in
prevalence between men and women when respondents
were divided into different age and income groups, but
male respondents had steeper relationship between
advanced age and diabetes prevalence than females.
Thirdly, those with low household income were twofold
more likely to report diabetes when compared with those
having the highest income.
Relationship with literature and explanations
of findings
The prevalence of diabetes in China was 5.5 % in the years
2000–2001 (Gu et al. 2003), a figure twice of that reported
10 years ago (Pan et al. 1997). Janus et al. (2000) conducted
a population-based study in Hong Kong involving
2,900 Chinese persons aged 25–74 years in 1995–1996
using a 75 g oral glucose tolerance test, and found a
prevalence rate of 6.2 % (95% CI 5.3–7.1 %) using the
American Diabetes Association criteria (1997). However,
the prevalence figures were 9.2 (95% CI 8.1–10.3 %) and
9.8 % (95% CI 8.7–10.9 %), respectively, using the WHO
(1995) and WHO (1998) criteria. Our study used selfreported
information and it was therefore difficult to
Table 2 Prevalence of self-reported diabetes among male adults
aged C15 years (N = 50,427) in the household face-to-face interviews
conducted in Hong Kong, China by stratified random sampling
of living quarters in the territory in the years 2001, 2002, 2005 and
2008
Age (years) 2001 2002 2005 2008
% SD % SD % SD % SD
15–24 0.13 3.57 0.05 2.32 0.09 3.02 0.09 3.02
25–34 0.12 3.45 0.14 3.77 0.26 5.10 0.06 2.51
35–44 0.79 8.87 1.02 10.05 1.11 10.47 1.36 11.59
45–54 2.34 15.19 2.31 15.03 2.79 16.46 3.85 19.24
55–64 6.84 25.39 6.87 25.30 6.20 24.12 8.73 28.22
65–74 11.18 31.51 10.45 30.59 11.26 31.61 17.56 38.05
C75 10.90 31.16 13.24 33.89 13.93 34.63 16.12 36.77
Adults C15 2.80 16.35 2.87 16.69 3.32 17.90 4.66 21.08
The table shows the age-specific prevalence of self-reported diabetes
across different years
SD standard deviation
Table 3 Prevalence of self-reported diabetes among female adults
aged C15 years (N = 52,895) in the household face-to-face interviews
conducted in Hong Kong, China by stratified random sampling
of living quarters in the territory in the years 2001, 2002, 2005 and
2008
Age (years) 2001 2002 2005 2008
% SD % SD % SD % SD
15–24 0.04 2.04 0.12 3.44 0.17 4.07 0.11 3.27
25–34 0.14 3.69 0.43 6.57 0.15 3.93 0.27 5.18
35–44 0.63 7.92 0.66 8.08 1.08 10.33 0.58 7.57
45–54 2.69 16.24 2.13 14.45 2.16 14.54 2.41 15.35
55–64 9.63 29.52 7.95 27.05 7.00 25.52 8.31 27.60
65–74 13.24 33.90 14.02 34.72 14.66 35.37 15.15 35.85
C75 12.07 32.57 14.05 34.75 15.91 36.58 20.44 40.33
Adults C15 3.25 17.44 3.37 18.04 3.77 19.04 4.31 20.32
The table shows the age-specific prevalence of self-reported diabetes
across different years
272 M. C. S. Wong et al.
123
compare with findings from other studies. However, the
rising trend of diabetes across the years from 2001 to 2008
in this study was in general compatible with results
from other surveys. Increasing prevalence rates have previously
been reported in the US (Cowie et al. 2006; Harris
et al. 1998), Australia (Dunstan et al. 2002), Denmark
(Drivsholm et al. 2001), the Indian city of Chennai (Ramachandran
et al. 1997; Mohan et al. 2006) and the Indian
Ocean island of Mauritius (Soderberg et al. 2005).
The escalating prevalence of diabetes from the current
findings could be due to increasing incidence over time.
Some of the reasons include population ageing and rapid
urbanization, which is associated with lifestyle changes
including unhealthy diet, physical inactivity, obesity and
sedentary habits (Gu et al. 2003). On the other hand, it
might be attributed to a better primary healthcare system in
Hong Kong which detected diseases early among the
younger individuals with risk factors, fundamentally due to
heightened awareness of earlier diagnosis and more
effective community-based health educational programs.
Nevertheless, reduced mortality has also been suggested as
a contributing factor to the rising prevalence, and recent
opinions are mixed as to what factors are the most influential
(Colagiuri et al. 2005; Wareham and Forouhk 2005;
Green et al. 2005; Gale 2003). Demographic changes are
not sufficient to explain the rising rates, and hence there is
a need for future studies capturing age-specific incidence
data for the same population likely to have experienced the
same risk factor changes over distinct time periods
(Wareham and Forouhk 2005).
The current literature involving larger-scale population
surveys do not demonstrate a consistent difference between
male and female in the prevalence of diabetes, and a largescale
study in China by Gu et al. (2003) showed a statistically
similar age-standardized prevalence of self-reported
diabetes between the two genders. In addition, it is of
interest to note that with increasing age, the prevalence of
diabetes in males increased more sharply than females.
This observation is yet to be addressed by future studies.
Our study clearly showed that the lowest income group
suffered from much higher risk of diabetes. A populationbased
survey conducted in the UK studying socioeconomic
status and its relationship with diabetes (Connolly et al. 2000)
showed that the prevalence of type 2 diabetes was around
30 % higher in residents living in regions with the worst
quintile of deprivation scores when compared with residents
in the richest area. Similar conclusionswere echoed by studies
based on a diabetes register in Scotland (Evans et al. 2000) and
general practices in Spain (Larranaga et al. 2005). However,
the influence of socioeconomic deprivation on diabetes
seemed to run in opposite direction in the developing nations.
A study in India highlighted that those in the high income
group were twofold more likely to have diabetes than the
lower income group residents (American Diabetes Association
2010), while another study in theMainland China showed
the similar higher risk among the rich. It has been postulated
that in developed countries, those living in districts of deprivation
have poorer access to health information and healthcare
services, thus consuming lower cost, yet less healthy, energydense
diets (Feinglos and Bethel 2007). In developing
Table 4 Adjusted prevalence
of self-reported diabetes by
monthly household income and
sex for all respondents in the
household face-to-face
interviews conducted in Hong
Kong, China by stratified
random sampling of living
quarters in the whole territory in
the years 2001, 2002, 2005 and
2008
a Adjusted prevalence refers to
population adjustment by
monthly household income
Monthly household income
(HK dollars)
Year Adjusted prevalencea (%, SD)
Male (n = 58,854) Female (n = 60,572)
% SD % SD
C50,000 2001 1.37 11.47 1.46 11.75
2002 1.98 13.95 1.11 10.48
2005 1.26 11.17 2.67 16.12
2008 1.80 13.30 1.68 12.85
25,000–49,999 2001 1.72 12.91 2.21 14.43
2002 1.75 13.10 2.06 14.21
2005 2.35 15.14 2.04 14.13
2008 2.86 16.66 2.09 14.29
10,000–24,999 2001 1.87 13.89 2.41 15.14
2002 1.90 13.37 2.50 15.48
2005 2.16 14.55 2.87 16.68
2008 3.25 17.73 3.40 18.13
B9,999 2001 4.83 18.76 5.1 19.92
2002 4.60 19.28 5.11 20.50
2005 6.50 24.66 6.37 24.43
2008 8.97 28.57 8.28 27.56
Rising tide of diabetes mellitus in a Chinese population 273
123
countries, poorer residents are more likely to be employed in
manual work with limited access to labor-saving facilities.
This increase in physical activity, together with the higher
consumption of fruit and vegetables among the poorer may
explain their lower prevalence of diabetes in developing
nations (Feinglos and Bethel 2007).
Strengths and limitations
This study included the data of a total of more than 121,000
respondents collected in surveys and the standardized
methods used with proper interviewer training were
identical across different time periods. The populationbased
random sampling method facilitated generalizability
of our findings, and the statistical adjustment made to the
prevalence figures minimized the effect of demographic
changes in different years. However, several limitations
should be mentioned. First, we relied on self-reported
information to ascertain the prevalence of diabetes, and
recent studies in China suggested three out of four diabetes
patients were undiagnosed (diagnosed diabetes 1.3 % vs.
undiagnosed diabetes 4.2 %) (Gu et al. 2003). Thus far
there has been no information in any sub-populations on
the validity of self-reported diabetes when compared with
Table 5 Factors associated with self-reported diabetes among all respondents in 2008 in the household face-to-face interviews conducted in
Hong Kong, China in the year 2008 by stratified random sampling of living quarters in the whole territory
Total no. Diabetes
reported
% Adjusted odds
ratios
95% CI P value
All respondents (N = 28,923; R2 = 0.198)
Age (years)
0–39 13,741 20 0.15 1 Referent
40–65 11,479 527 4.59 32.21 20.59–50.37 \0.001
[65 3,703 636 17.18 120.08 76.6–188.26 \0.001
Sex
Female 14,734 580 3.94 1 Referent
Male 14,189 603 4.25 1.10 0.97–1.24 NS
Monthly household income (HK dollars)
C50,000 3,455 64 1.85 1 Referent
25,000–49,999 7,886 206 2.61 1.39 1.04–1.86 \0.05
10,000–24,999 11,873 414 3.49 1.58 1.2–2.07 \0.001
B9,999 5,709 499 8.74 2.19 1.66–2.88 \0.001
Male respondents (n = 14,189; r2 = 0.191)
Age (years)
0–39 6,720 8 0.12 1 Referent
40–65 5,678 296 5.21 45.43 22.49–91.79 \0.001
[65 1,791 299 16.69 141.08 69.47–286.48 \0.001
Monthly household income (HK dollars)
C50,000 1,686 33 1.96 1 Referent
25,000–49,999 3,888 119 3.06 1.59 1.07–2.36 \0.05
10,000–24,999 5,890 203 3.45 1.51 1.03–2.21 \0.05
B9,999 2,725 248 9.10 2.28 1.55–3.35 \0.001
Female respondents (n = 14,734; r2 = 0.208)
Age (years)
0–39 7,021 12 0.17 1 Referent
40–65 5,801 231 3.98 23.49 13.13–42.02 \0.001
[65 1,912 337 17.63 105.45 58.91–188.77 \0.001
Monthly household income
C50,000 1,769 31 1.75 1 Referent
25,000–49,999 3,998 87 2.18 1.20 0.79–1.83 NS
10,000–24,999 5,983 211 3.53 1.66 1.13–2.45 \0.05
B9,999 2,984 251 8.41 2.14 1.44–3.16 \0.001
Self-reported diabetes was the outcome of interest with age, sex and monthly household income as independent variables
274 M. C. S. Wong et al.
123
standardized methodology. In addition, there were other
variables which could influence the prevalence of diabetes
not taken into account in our study, including lifestyle
factors, body mass index and family history of diabetes.
Also, this survey adopted a study design by stratified random
sampling. The regression analyses explained
approximately 20 % of the variability of diabetes prevalence,
and more work is needed to explore its relationship
with other risk factors in this large Chinese population.
Implication to clinical practice and policy-making
Our findings have important public health implications. The
development of the micro- and macro-vascular diabetes
complications leads to a huge burden to the society (American
Diabetes Association 2010). The rising prevalence of
diabetes detected in this study signals a need for more
extensive community-based educational programs especially
targeted towards the higher risk group. In addition, the
promotion of clinical guidelines in primary care is a crucial
step towards clinic-based diabetes screening for the early
detection of diabetes and impaired glucose tolerance. In
Hong Kong, a recent reference framework for diabetes care
in primary care setting has been developed and promulgated
in clinical practice (Hong Kong Reference Framework
2011). Future research will need to evaluate the impact of
primary care initiatives to combat the rising trend of diabetes
by engaging different stakeholders of the healthcare system
(Hong Kong Reference Framework 2011).
In summary, this study found an increasing prevalence
of diabetes from 2001 to 2008, and we have reasons to
anticipate that this trend will continue to rise. These findings
cautioned the need to formulate territory-wide
strategies to improve prevention, detection and treatment
of diabetes by more intensive, concerted efforts of the
multidisciplinary primary care teams.
Conflict of interest The authors declare that they have no conflict
of interest.
Ethical standards The surveys comply with the current laws of the
country in which they were performed.
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276 M. C. S. Wong et al.
123
Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.
Alcohol and other drug use at school leavers’ celebrations
Tina Lam,Wenbin Liang, Tanya Chikritzhs, Steve Allsop
National Drug Research Institute, Curtin University, Perth, WA 6845, Australia
Address correspondence to Tina Lam, E-mail: [email protected]
ABSTRACT
Background A significant proportion of adolescents who attend celebratory events often engage in substantial alcohol and other drug use.We
examined patterns, influences and impacts of drug consumption at an end of schooling life celebration.
Methods Seventeen- to 18-year-old Australians who intended to attend (n ¼ 541) and who attended the celebration (n ¼ 405), respectively,
completed pre- and post-event surveys.
Results Males consumed 18.44 and females 13.24 Australian standard drinks on an average day during the school leavers’ event. Compared
with their last social event, there was greater alcohol (P, 0.0005) and ecstasy use (P, 0.046 for Day 1 and P, 0.008 on Day 3). However, the
number of drinks consumed per hour appeared to be similar across contexts. Most (87%) experienced at least one negative outcome attributed to
alcohol and other drug use. Safety strategies were frequently used and appeared to be protective against some of the most common harms
(hangover, vomiting, black out and unprotected sex).
Conclusions The use of alcohol and other drugs at this celebratory event appears to be reflective of the greater than usual number of drinking
hours that are available to participants. The use of safety strategies can be successful in mitigating some of the most common drug-related harms.
Keywords alcohol consumption, celebration, health promotion, large event, leavers, protective behavioral strategies, risky single occasion
drinking, schoolies, young people
Introduction
Adolescent alcohol use in countries such as the USA, UK and
Australia, is typified by episodic consumption, which commonly
occurs to the point of intoxication.1 – 4 This style of ‘risky
drinking’ means that young people are frequently affected by
blackouts (memory loss), hangovers and violence.5,6
Adolescent alcohol and other drug (AOD) use appears to
peak at ‘special events’.7,8 For many young adults in Western
countries, the milestone of school completion is marked by
festive events. These multiple day celebrations are a much
anticipated occasion for frivolity with fellow alumni; and, in
Australia, up to half of all Year 12 graduates attend some form
of these school leavers’ (also known as ‘Schoolies’ or ‘Leavers’)
celebrations.9,10
Compared with the significant press coverage each year,11
there has been relatively little formal research into the phenomenon.
The common theme of existing studies is that for a
significant proportion of attendees, the event revolves around
heavy alcohol use, some consumption of other drugs and
engagement in other risky behaviours such as unprotected casual
sex.12–20 Similar scenarios occur at other multiple-day peer-based
celebratory events such as Spring Break in the USA,21,22 and
russefeiring, a 17-day Norwegian graduation party.23
These risky behaviours are partially attributed to the
‘holiday effect’, a phenomenon where individuals on holiday
tend to engage in risky behaviours not otherwise attempted at
home.13,18,24 – 27 These elements include the temporary suspension
of social codes, such as responsibility and accountability;
time away from usual authority figures; a peer-based
environment and a reputation for AOD experimentation.
Also, heavier drinkers appear to ‘self-select’ to attend party
destinations with a reputation for AOD use.28 – 31
Tina Lam, Research Associate
Wenbin Liang, Research Fellow
Tanya Chikritzhs, Professor and Project Leader
Steve Allsop, Professor and Director
408 #The Author 2013. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: [email protected].
Journal of Public Health | Vol. 36, No. 3, pp. 408–416 | doi:10.1093/pubmed/fdt087 | Advance Access Publication 27 August 2013
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Currently, there are few international and no Australian peerreviewed
published studies which provide quantity-specific estimations
that reliably gauge the extent of AOD use at school
leavers’ celebrations (especially alcohol), and provide a fulsome
view of its influence on behaviour.
The aims of this study were therefore to (i) compare the
levels of AOD use at an end of school celebration and use at
other peer-based social events and (ii) relate the experience
of harms experienced at the celebrations to levels of use and
engagement in harm-minimization strategies.
Methods
Design
Core data for this project were gathered using a two-part
survey design with a self-report methodology. The majority of
the respondents were aged 17 (legal purchase age for alcohol
in Australia is 18).32 Respondents intended to, and/or had
attended the 2009 school leavers’ celebrations on Rottnest
Island. This Island is located 20 km off the west coast of
Perth and is a popular location for the event in Western
Australia. This location was chosen as the bulk of the visitors
entered and exited via a single ferry terminal. This ‘bottlenecking’
facilitated survey administration.
The first survey sampled young people who intended to
attend the event (n ¼ 541; 56% female; 91% 17 years and 9%
18 years of age; 87% enrolled in an independent school). This
pre-celebration survey was available both online and face to face.
Half (52%) were conducted online from 2 months to the day
prior to the celebration. The mean online completion time was
15.64 min [95% CI (14.79, 16.49), n ¼ 215 (outliers removed)].
The remaining paper surveys were disseminated on the first day
of the celebrations on five ferries travelling to Rottnest Island.
Project information forms and blank surveys were provided
en route, and completed surveys collected as the boat docked.
The post-celebration survey was completed by 405 (50%
female; 94% 17 years of age and 6% 18 years and over; 92%
attended an independent school). While this second survey
was also available online, most (86%) were conducted face to
face. On the last day of the event, a team of 27 researchers
distributed surveys around the island’s accommodation, commercial
areas and ferry terminal. Researchers remained within
a visible distance to participants to encourage serious attempts
and to collect surveys. Face-to-face response rates were estimated
at 90% and the completion time at 15 min. Survey
modality (online versus face-to-face) was controlled for multifactorial
analyses, and Wilcoxon–Mann–Whitney tests did
not reveal any significant differences in intended or reported
actual alcohol use across the modalities.
The two surveys were designed to be analysed primarily as
separate components—one assessing intentions and the
other what happened at the celebrations. As the total number
of celebrants on the island was 1466, _37% of the population
was surveyed with the pre-celebration survey and 28%
for the post-celebration survey. Although recapture was not a
central method of the study, a self-generated anonymous
code was incorporated into both instruments to pair an individual’s
data where possible.33,34 Not all participants completed
the code and the pre- and post-event surveys of 120 participants
were eventually linked (62% female). Due to the
modest known paired sample size, most analyses focus on
‘within-survey’ data (combining both paired and unpaired
respondents).
Confectionaries (‘lollies’) were provided as a minor incentive
with face-to-face surveys. Participants of both survey modalities
were able to enter a voucher prize draw. Prize-draw
email addresses were detached from or collected in separate
databases to the survey data. Consent was implied by survey
completion.35 This study was approved by Curtin University
(HR135/2008) and the Rottnest Island Authority (2008/13;
2009/110328).
Measurements
Both surveys contained psychometrically validated and novel
items in Likert and free response form. The pre-celebration
survey included quantity-specific expectations of personal and
peer AOD use at the event; expectations of how permissive the
celebration context would be; parental discussions about
alcohol use and AOD use at their last social event. This ‘last
event’ was the last social occasion attended with friends prior
to the school leavers’ celebration. As adolescent alcohol use
tends to be episodic and increase in ‘party’ contexts,5,36 the
more frequently used survey reference period of the last 7
days37 may or may not include a peer-based social event. The
school leavers’ celebration and the last event were comparable
in that they were both social and peer based, and assessed a
similar subset of young people who had self-selected as intending
to/attended the end of school celebrations.19,38 That is, the
‘last event’ served as a proxy for ‘usual’ AOD behaviour.
The post-event survey investigated AOD use, perceptions
of peer AOD use, experience of AOD-conducive conditions,
negative consequences and harm reduction strategies employed
at the celebrations.
Alcohol consumption was estimated using validated tools
from the National Drug Strategy Household Survey—the
beverage-specific and the standard drink (SD) approach.39,40
The beverage-specific method requires the respondent to
specify their drink (e.g. mid-strength beer), the size of their
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drink receptacle (e.g. a 330 ml bottle) and the number of each
type consumed, in table labelled with the most common beverage
types and sizes. The SD method requires the respondent
to convert their intake into SDs and then to record a
figure that summarized daily consumption. The SD question
‘how many standard drinks did you have on Day 1?’ was
supplemented by a visual guide. In Australia, a ‘standard
drink’ contains 10 g of alcohol. Piloting confirmed that comprehension
of the ‘SD’ concept was high, as it was a part
of many schools’ syllabus. The beverage-specific response
method is one of the most valid self-report measures of
alcohol quantity—however, its higher and more accurate estimates
are offset by a considerably lower response rate.41
Both estimates were presented in Table 1, but only the
beverage-specific estimates have been discussed. The beveragespecific
method was used for the last event and celebration estimates,
whereas the SD method was only used in the celebration
estimates.
Analysis
A series of Wilcoxon signed rank tests were performed to
compare AOD use between the contexts of the last event and
an average day at the leavers’ celebrations (paired respondents).
Logistic regression analyses were performed to assess the
impact of six factors on the likelihood of reported experience
of 17 negative consequences. Independent variables were
chosen to assess the ability of safety strategies to attenuate experience
of a variety of harms. The six variables contained in
each model were as follows: (i) an average quantity of alcohol
used on a single day at the event; (ii) use of drugs other than
alcohol; (iii) use of alcohol-related safety strategies, as assessed
using the Protective Behavioural Strategies Survey (PBSS).
The PBSS is a psychometrically validated list of behaviours that
minimize alcohol use and related acute harm42–48 (iv) gender;
(v) accommodation location and (vi) survey administration
modality (online or face to face).
Results
Alcohol use at leavers’ celebrations and the
last event
A significantly greater proportion of respondents used
alcohol during the celebration period (93%) and on each celebration
day (an average of 88% across the 3 days), compared
with the last peer-based social event (78%).
Using the beverage-specific response method, drinking
respondents were estimated to have consumed a mean of
11.94 SDs at their last social event, and 15.80 SDs on an
average celebration day (see Table 1 and Fig. 1). Paired
respondents consumed an average of 5.07 SDs more in the
celebration context compared with their last event (95% CI
2.92, 7.23); Wilcoxon signed rank test statistics: z ¼ 24.38,
n ¼ 58, P ¼ 0.0005, r ¼ 0.59 [(large effect)].
Respondents were asked to specify the number of hours
over which drinking occurred. A mean of 5.37 drinking hours
was reported for the last event (n ¼ 361) and 7.42 (n ¼ 356)
Table 1 Alcohol use at the last social event and on an average day at the school leavers’ celebrations
Alcohol
estimate
method
Males Females All drinking respondents
Mean 95% CI Missing
n
n Mean 95% CI Missing
n
n Mean 95% CI Missing
n
n
Last event Beverage
specific
14.32 12.73,
15.89
58 132 10.09 9.00,
11.17
61 170 11.94 11.01,
12.88
123 306
Average school
leavers’ event day
Beverage
specific
18.44 16.72,
20.16
67 118 13.24 11.64,
14.84
63 122 15.80 14.60,
17.00
133 242
SD 17.05 15.57,
18.53
13 172 11.44 10.24,
12.64
11 174 14.20 13.20,
15.19
27 348
Note: means and CIs calculated with respondents who used alcohol (112 at the last event and 30 at the school leavers’ event did not drink). Estimates
include both paired and unpaired respondents. Some did not specify their gender (four at last event and two at school leavers’ event). Mean alcohol use at
school leavers’ event was highly correlated across the beverage-specific and SD response methodologies (Spearman’s rho ¼ 0.87, P, 0.005, n ¼ 235). A
similar proportion of males and females consumed alcohol at both the last event and the end of school celebrations. However, in both contexts, males
consumed significantly more: 4.23 SDs at the last event and by 5.20 SDs on an average celebration day (P ¼ 0.0005). In Australia, the National Health and
Medical Research Council States a threshold of no more than four SDs for low-risk single occasion alcohol consumption. The clear majority of the drinkers
consumed beyond this guideline on an average celebration day (87% using the SD method and 91% using the beverage-specific method).
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for an average celebration day. Unsurprisingly, there was a
positive correlation between the average number of drinking
hours and quantity of alcohol consumed at the celebration
(Spearman’s rho ¼ 0.62, n ¼ 239, P, 0.0005), and at the last
event (Spearman’s rho ¼ 0.30, n ¼ 300, P, 0.0005)
A drinking pace score was calculated to indicate the
number of SDs consumed in 1 h. The mean drinking pace at
the last event was 2.91 (95% CI 2.62, 3.19; n ¼ 300) and 2.70
(95% CI 2.50, 2.90; n ¼ 238) on a mean celebration day. On
average, there was a smaller than 10% difference in the drinking
pace between the contexts of the last event and the celebration
(combining the scores of paired and unpaired respondents).
Wilcoxon signed rank tests did not reveal any significant differences
in paired respondents’ drinking pace across contexts.
Drugs other than alcohol at school leavers versus
the last event
The use of amphetamine, caffeine, cannabis and ecstasy were
assessed dichotomously. In these analyses, the use of ‘an illicit
drug’ was defined as the use of amphetamine and/or cannabis
and/or ecstasy. Thirteen per cent used an illicit drug at
their last event, 14% used an illicit drug on an average celebration
day (mean use over Days 1–3) and 20% used on any one
celebration day (see Table 2).
A series of Wilcoxon signed rank tests were used to contrast
paired respondents’ use of each drug across the contexts
of their last event and each individual celebration day.
Paired respondents were more likely to use ecstasy on Day 1
[z ¼ 22.00, paired n ¼ 103, P ¼ 0.046, r ¼ 0.14 (small
effect size)] and Day 3 of the celebrations [z ¼ 22.65, paired
n ¼ 103, P ¼ 0.008, r ¼ 0.18 (small–medium effect size)]
compared with the last event they attended. No other comparisons
were significantly different.
Negative consequences and the use of protective
strategies
The majority of respondents (87%) experienced at least one
negative experience at the school leavers’ celebrations that they
attributed to AOD use (n ¼ 313, 92 missing; see Table 4).
Table 4 provides a summary of the logistic regression analyses
associated with the experience of negative outcomes. Some independent
levels had more than two levels. Alphabetical letters
were used in Table 3 to denote each comparison between levels
of the same variable (e.g. to compare the highest and lowest
quartiles of alcohol use). These letters were used and so odds
ratios are identified with a specific level of a variable, rather than
with the variable as a whole. For example, the cell content of
‘9.34**b’ in Table 4 relates back to the letter ‘b’ in Table 3. It
means that respondents who drank 11.67–18.33 SDs (‘b’) were
9.34 times as likely to report a blackout compared with those
who drank 0–6.00 SDs (comparison/reference group).
Incidentally, this blackout finding is consistent with previous
findings that adolescent drinkers are more susceptible to
0
5
10
15
20
25
30
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
Percentage of respondents
Standard drinks consumed
Last event (n=418)
Average school leavers’
celebration day (n=272)
Fig. 1 Alcohol use at the last event and on an average day at the school leavers’ celebrations. Note: alcohol consumption estimates made using the
beverage-specific approach with all paired and unpaired respondents. Alcohol consumed was assessed on a continuous scale. Values above zero were placed in
categories representing two SDs. SD labels reflect the highest value within each category, i.e. ‘2’ represents the values between 0.01 and 2.00.
SCHOOL LEAVERS’ CELEBRATIONS 411
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blackout compared with adults,30 and supported by data from
a recent nationally representative survey.40
Of the 17 outcomes that were assessed, 14 models were
significant. Four negative consequences were uniquely associated
with the use of safety strategies: hangover, vomiting,
blackouts and unprotected sex.
Controlling for all other factors in the model and compared
with those who engaged in safety strategies with the greatest frequency
(the reference group), the following odds ratios (OR)
were reported. Respondents who engaged in protective strategies
with the lowest frequency were: 3.50 times more likely to
report a hangover; 3.38 times more likely to report a blackout
and 10.92 times more likely to report unprotected sex. Those
who engaged in protective strategies with the second greatest
frequency were 2.61 times more likely to report vomiting.
Discussion
Main finding of this study
The majority of the school leavers were consuming very high
levels of alcohol. Using one of the most accurate methods
of self-report, a daily mean of 18.44 Australian SDs was
reported for males and 13.24 for females.
What is already known on this topic
The proportion of alcohol users (93%) is similar to other
Australian Schoolies studies, which range from 90 to
97%.19,20,49 – 51 In Victoria and Queensland, 69 and 76%
reported consuming 5þ drinks on a ‘typical’ Schoolies day.16,20
The estimates in this study are substantially higher, but are
likely a result of methodology differences. For example,
Table 2 Use of drugs other than alcohol at the last event and at Leavers
Last event Leavers day 1 Leavers day 2 Leavers day 3 Any one day at Leavers
% n % n % n % n % n
Males
Amphetamine 9.52 189 13.25 166 7.05 156 5.73 157 15.38 169
Caffeine 41.49 188 47.53 162 37.27 161 35.67 157 56.07 173
Caffeine and alcohol 53.73 67 75.47 53 87.50 40 76.67 30 78.95 76
Cannabis 15.14 185 15.43 162 14.29 154 10.46 153 22.35 170
Ecstasy 4.81 187 10.91 165 9.55 157 10.32 155 16.47 170
Other drugs 3.87 181 7.43 148 3.45 145 2.78 144 9.55 157
An illicit drug 18.85 191 22.89 166 18.87 159 16.56 157 27.57 185
Females
Amphetamine 3.07 261 3.49 172 2.99 167 3.53 170 6.86 175
Caffeine 39.31 262 39.41 170 32.72 162 36.09 169 50.86 175
Caffeine and alcohol 59.14 93 70.45 44 68.57 35 67.44 43 71.23 73
Cannabis 5.75 261 6.59 167 3.64 165 3.05 164 8.05 174
Ecstasy 2.33 257 4.68 171 4.24 165 7.14 168 8.57 175
Other drugs 2.49 241 0.00 156 0.00 153 0.65 155 0.60 166
An illicit drug 8.78 262 9.88 172 6.59 167 10.18 167 13.66 183
All respondents
Amphetamine 5.74 453 8.24 340 4.92 325 4.56 329 10.98 346
Caffeine 40.44 455 43.11 334 34.98 323 35.67 328 53.14 350
Caffeine and alcohol 56.79 162 73.20 97 78.67 75 71.23 73 75.17 149
Cannabis 9.78 450 10.88 331 8.72 321 6.58 319 15.03 346
Ecstasy 3.57 448 7.69 338 6.79 324 8.62 325 12.39 347
Other drugs 3.06 425 3.59 306 1.67 300 1.66 301 4.92 325
An illicit drug 13.13 457 16.18 340 12.50 328 13.19 326 20.49 371
Note: n represents valid responses—whether the drug was used or not used. An ‘illicit drug’ was the use of amphetamine and/or cannabis and/or ecstasy.
Estimates for ‘caffeine and alcohol’ reflect a subset of caffeine users. Compared with females, males were more likely to have used: amphetamine at the
last event (P ¼ 0.007) and at the end of school celebration (P ¼ 0.01); cannabis at the last event (P ¼ 0.002) and at the celebration (P ¼ 0.0005); ecstasy at
the celebration (P ¼ 0.04); a drug other than those listed at the celebration (P ¼ 0.001) and an illicit drug at the last event (P ¼ 0.003) and at the
celebration (P ¼ 0.002).
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compared with these other studies, this instrument (i) utilized
the SD and beverage-specific method as opposed to multiple
choice options (5 brackets, the highest being 10þ), (ii) used the
concept of the ‘SD/used a SD visual guide and (iii) referred to
a specific as opposed to a ‘typical’ day.
These results are broadly consistent with estimates using
similar quantity-specific measures. For example, the average
alcohol use per celebration day did not appear to be substantially
different from Spring Break estimations of 18 drinks for
males and 10 drinks for females.22 While an Australian SD contains
10 g of alcohol and US drinks contain _12 g of alcohol,
the studies taken together suggest broad similarity and potentially
some convergence in drinking rates between the genders.52
What this study adds
As the drinking rates (SDs per hour) appeared similar to the
last social event attended, it is possible that the longer hours
available at the celebratory event accounted, to some extent,
for the substantial quantities of alcohol consumed. As there is
some research evidence to support the notion that longer
drinking hours are associated with higher levels of consumption,
53 it is reasonable to propose that a greater opportunity
to drink may have directly facilitated the greater use of alcohol
per day. As celebrating students were commonly observed to
commence drinking in the late afternoon, an earlier start time
may be the key influence. These longer drinking times are
possibly in turn fostered by lack of usual academic responsibilities,
parental supervision and being within an environment
with a reputation for heavy drinking.
The reported prevalence of ecstasy use at school leavers’ celebrations
was roughly twice that of the last social event.
Although the reasons for higher ecstasy use were not specifically
examined in this study, it is possible for example, that
ecstasy’s effects of increased ‘cheer and chatter’ and as an antisoporific,
aid what is regularly cited as the main positive aspect
of leavers’ celebrations: to socialize with peers.14,54,55 The
absence of other drug differences between contexts are mostly
unsurprising due to the lower frequency of illegal drug use in
this age group combined with the paired sample size.56,57
Encouragingly, not only were the alcohol-related safety
strategies frequently used, they appeared to have a protective
effect. Controlling for a range of potential confounders, the
use of protective harm reduction strategies was associated
with lowered odds of experiencing some of the most
common harms and risks including hangover, vomiting,
blackouts and unprotected sex.
This study uniquely provided quality documented variation
in use patterns, and risk and protective factors associated with
riskier levels of use. This study was distinctive in using the last
social event attended with friends as a behavioural baseline to
identify a range of factors differentiating between contexts.
Limitations of this study
Although self-report measures are considered a generally
valid measure for adolescent drug use,58 – 60 there are some
potential limitations. First, deliberate misreporting is an issue
Table 3 Variables used in logistic regression models associated with
experience of negative outcomes
Independent variable Category value Parameter coding n
(1) Alcohol use on an
average celebration day
0–6.00 SDs Comparison/
reference group
96
6.33–11.33 a 92
11.67–18.33 b 89
18.67–45.00 c 101
(2) Other drug use No other drugs
used
Reference group 167
Caffeine used
(no illicits)
d 127
Illicits used (+
caffeine)
e 76
(3) PBSS (Protective
Behaviour Strategy Score)
Scores 14–46
(safest)
Reference group 63
Scores 47–56 f 65
Scores 57–65 g 59
Scores 66–84
(least safe)
h 61
(4) Gender Female Reference group 200
Male 200
(5) Accommodation
location
Main
settlement area
Reference group 287
Secondary
region
110
(6) Survey modality Online Reference group 55
Face to face 350
Note: alcohol use was assessed using the ‘SD response method’ to
maximize the sample size available for analysis. The letters in the
parameter coding column relate to the superscript in Table 4. These
letters denote which levels of each IV were significant when compared
with the reference group. The PBSS asks respondents to indicate on a
6-point Likert scale whether they engaged in the set of safety behaviours
while drinking.Minor alterations were made to the PBSS tomake it
relevant to the sample and context, and a test–retest procedure (n ¼ 20)
and a Cronbach’s alpha of 0.83 for the PBS summary score with the final
data set (n_260) suggest these changes did not affect the reliability of the
scale. Bookings for the two accommodation locations were randomly
allocated, but the sites differed in terms of accessibility by support services
etc. Continuous IVs (alcohol use and PBSS) were split into quartiles to
facilitate logistic regression analyses with evenly sized groups.
SCHOOL LEAVERS’ CELEBRATIONS 413
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Table 4 Likelihood (OR) of negative consequences associated with AOD use and other risk factors at the school leavers’ celebration
Consequence (DV) Descriptives Odds ratios (OR) for the significant unique associations
Prevalance
(%)
n Alcohol use (0–6 SDs) Other drugs
(none)
Safety strategy
use/PBSS
(safest)
Gender
(female)
Location (main
settlement)
Survey modality
(online)
Hangover 67.42 310 2.67*a [1.14, 6.22], 3.18*b [1.23,
8.22], 5.55**c [1.76, 17.48]
— 3.50*h [1.21,
10.11]
— — 0.33* [0.12,
0.91]
Emotional outburst 45.28 307 — 3.98**e [1.62, 9.80] – 0.29** [0.16,
0.54]
— —
Vomiting 37.91 306 — — 2.61*f [1.13,
6.03]
— — —
Heated argument 35.69 297 4.01*b [1.36, 11.82] 2.29*d [1.15, 4.55],
5.52**e, [2.09, 14.56]
— — — —
Accident/injury 40.67 300 — 2.46**d [1.29, 4.72] — 0.39** [0.21,
0.73]
— —
Physically aggressive 18.98 295 — 4.04*e [1.27, 12.82] — 0.31* [0.13,
0.78]
— —
Blackout 57.95 302 2.66*a [1.05, 6.73], 9.34**b [3.29,
26.51], 6.22**c [1.98, 19.55]
— 3.38*h [1.22,
9.40]
— — —
Inability to pay for things 12.29 301 — 4.49*e [1.17, 17.27] — — — —
Unprotected sex 13.62 301 — — 10.92*h [1.14,
104.23]
— — —
Sexual situation was not happy
about at the time
15.38 299 — — — — — —
Regretted sexual encounter 21.33 300 — — — — — 0.37* [0.14,
0.98]
Stole private/public property 12.42 298 — 10.08**e [2.45, 41.47] — — — —
Act of vandalism 9.70 299 — 7.75*e [1.51, 39.78] — — 4.03* [1.19, 13.67] —
Removed from island/
accommodation
3.33 300 — — — — — —
Arrested for intoxicated
behaviour
5.02 299 — — — — — —
Any sexual risk/problem 32.23 301 — 2.95*e [1.17, 7.47] — 0.49* [0.25,
0.96]
— —
Any legal problem 18.27 301 — 9.71**e [3.16, 29.85] — — — —
Note: all logistic regression analyses control for alcohol quantity, other drug use, safety strategy use, gender, location and survey modality. Reference groups are presented in brackets after each independent
variable. 95% CI presented in square brackets after the odds ratio. The logistic regression models were not statistically significant for the following: (i) sexual situation was not happy about at the time, (ii)
removed from island/accommodation and (iii) arrested for intoxicated behaviour. ‘Any sexual risk/problem’ was a summary variable (endorsement of at least one of the following: unprotected sex, sexual
situation they were not happy about at the time or sexual encounter they later regretted). ‘Any legal problem’ was a summary variable (endorsement of at least one of the following: stealing, vandalism,
removal/banning or arrest).
‘—’ symbol denotes the independent variable did not make a significant unique contribution to the model.
*A significant unique association where P , 0.05 (**for when P, 0.01).
414 JOURNAL OF PUBLIC HEALTH
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for all self-administered surveys, underreporting and over
reporting having potential to skew results.59 Secondly, recall
effects may cause reports of past behaviour may be incomplete/
inaccurate, even though the majority (96%) of the postcelebration
surveys were completed within 3 days of end of
celebrations. Lastly, though this study used an opportunistic/
convenience sample and cannot be conclusively stated as representative
of the celebrations, the combination of a high response
rate and that approximately a third of the total celebration population
was surveyed, remains a strength.
As school leavers’ celebrations show no obvious sign of
decline in popularity, recognition of actual and potential
harms, prevention and mitigation strategies are increasingly
important. They also have relevance for other celebratory
events. These findings have relevance identifying the high-risk
of celebration, demanding effective responses while simultaneously
indicating that use of harm reduction strategies can
reduce risk. Outcomes have been directly disseminated with
the celebration-coordinating government bodies to assist in
ensuring harm minimization and education are prioritized in
event management. Findings have also been translated into
practical strategies and communicated through national
media, and materials designed for parents and young people.
Funding
This project was supported by the Western Australian government.
The National Drug Research Institute at Curtin
University is supported by funding from the Australian
Government under the Substance Misuse Prevention and
Service Improvement Grants Fund.
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| Subject | Nursing | Pages | 18 | Style | APA |
|---|
Answer
IDENTIFYING AND INTERPRETING STATISTICS IN RESEARCH ARTICLES
Paper 1
Hypotheses
By definition, a null hypothesis is a collective statement shows that two incidences under investigation or consideration have no relationship (Sapkota, 2020). On the other hand, an alternative hypothesis is a statement that illustrates and interprets firmly; there is a relationship between two variables singled out in a specific study.
In the article Alcohol and Other Drug Use at School Leavers’ Celebrations, the null hypothesis in question is “The number of attendance of celebratory events by adolescents does not affect the alcohol and drug use.” (Lam et al., 2013). On the other hand, the alternative hypothesis is, “There is a relationship between alcohol and drug use in celebratory events by adolescents and negative outcomes of alcohol and drug use effects.”
Variables
With both hypotheses, null, and alternative, different variables were used. In the study presented by the article, independent and dependent variables were used for research purposes to verify or disagree with the hypotheses raised. In definition, independent variables, the leader of the research, will use variables that will change or control a dependent variable by directly affecting it (McLeod, 2019). The article presents six different independent variables that include Alcohol use on an average celebration day, Other drug use, PBSS (Protective Behaviour Strategy Score), Gender, Accommodation location, and Survey modality (Lam et al., 2013). These independent variables showcases in which the case subjects can change.
The null hypothesis is verified with each of the independent variables. Consequently, an increased number of adolescents engaging in alcohol and other drug use is directly proportional. Increased use of drugs and alcohol intake led to the increased undertaking of disruptive behavior. The control of alcohol and drug use in their bodily systems increased the level of engaging in disruptive behavior. This disruptive behavior results in the dependent variables in the research, which are the consequences of each independent variable.
Compared to independent variables, dependent variables can be viewed as the effect of the change in separate variables. Therefore, dependent variables will be tested and measured in experiments that rely on the independent variable as the cause; therefore, a dependent variable will be the resultant effect of the tested independent variable. In the article, dependent variables include the consequences of all included independent variables (McLeod, 2019). These, according to the report, include hangovers, emotional outbursts, vomiting, heated arguments, accidents and injuries, physical aggression, black outs, the inability to pay things, unprotected sex, regretted sexual encounters (Lam et al., 2013). The dependent variables include acts of vandalism, engaging in acts of theft by stealing private or public property, forceful removal of intoxicated persons from accommodation centers, arrests due to drunken behavior, sexual risks and problems, and legal issues for those arrested.
Sampling
The research team in this article articulates the use of stratified random sampling. This kind of selection is used for a specific demographic of a population. In this same demographic, people employed in the research study are picked randomly within this specified demographic. This sampling method aims to divide the total population into smaller groups to complete the data sampling needed to convene the aims of the study. In the article Alcohol and Other Drug Use at School Leavers’ Celebrations, the samples chosen for the study are divided into gender groups; males and females (Richland, 2019). Due to the sample size population being strictly adults, the gender sample size helps make sure that each of the adolescent students can answer the research questions.
Stratified random sampling is beneficial in making sure that it accurately reflects the under study’s sample population. By making sure that each subgroup is represented in the selection for the survey, better coverage of the population, in general, is seen. Ten researchers can easily ensure that each subset of the adolescent group under investigation is represented (MURPHY, 2020). On the other hand, stratified random sampling is not reliable for all studies in question in research. With members of an investigation being in more demographics, some studies prove insignificant in using this sampling system. Some specific studies may overlap with some found in two or more different subgroups of a particular population under investigation for a study by researchers.
Demographic characteristics
The researcher in this article paper on the study used different demographics. They include the sample population’s age, which was solely focused on adolescents aged between 17 and 18 years old. Also, the employed sex where both males and females of the said population were used for the study. Thirdly, the researchers focused on education for the sample population (Person, 2011). This was strictly academic students who were school leavers waiting to join universities and colleges in Australia.
Inferential statistics
Inferential statistics can be either estimated parameters or hypothesis tests. The article used both of these inferential statistics. Inferential statistics help researchers predict a sample of data on a covered (Stephanie, 2014). The estimated parameters used in the study were done by taking sample data and using it to conclude something on the total population being covered. For example, estimated statistics were used to complete that most adolescent s partook in alcohol and drug use after leaving school and engaged in disruptive behavior. Testing out hypotheses was also implemented in the results where dependent variables were drawn from the independent variables. The independent variables were based on both the null and alternative hypotheses, while the dependent variables showed the independent variables’ consequences.
Odds ratio
The odds ratio of unprotected sex was 10.92 times more likely to report unprotected sex. This means that the rate at which adolescents who engaged in alcohol and drug abuse were more likely to engage in unprotected sex due to informed decisions due to intoxication. Therefore, adolescents would take alcohol and drug use and end up with a higher rate of having unprotected sex according to the study compared to any other form of delinquency.
Representation
According to the study carried out by the sample size on the population of adolescents, most are engaging in the use of alcohol and drug use as that leads them into hangovers, emotional outbursts, vomiting, heated arguments, accidents and injuries, physical aggression, blackouts, the inability to pay things, unprotected sex, and regretted sexual encounters. Also, they engage in acts of vandalism, engaging in acts of theft by stealing private or public property, forceful removal of intoxicated persons from accommodation centers, arrests due to drunken behavior, sexual risks and problems, and legal issues for those arrested.
Paper 2
Aims of the study
The aims of the study can be restated as both null and alternative hypotheses. As a null hypothesis, the study depicts that, “Over the years between 2001 and 2008, age does not affect the rising cases of diabetes mellitus in the Chinese population.” (Wong et al., 2012). As an alternative hypothesis, the aims of the study can be restated as, “There is a relationship between the rise in cases of diabetes mellitus in the Chinese population with an increase in age as well as a decrease in household income.”
Demographic characteristics
The study was conducted under three major demographic characteristics. These are namely age, gender, and household income. Age as a demographic characteristic was focused on all age groups from children under 15 years to adults over the age of 65 years of age. Gender included both male and females from all ages. The range of household income included those who are well off – the rich- and the poor in the community in focus all over a vast range of the Chinese population.
Inferential statistics
The study uses estimated parameters as an inferential statistic for the study. The study covers a sample group over several years in the Chinese population. Considering that the Chinese overall population of over a billion people, estimated parameters are used to gain an understanding of trends in the Chinese population over a period stated in the study. This helps in making sure that the study covers all ages and time differences in transition of ages and people. The sample population used covers also changes in the economy and how it affects the spread of diabetes mellitus over the whole population of China (Lane, 2020). By use of confidence intervals, a high proportion of time is estimated on how the spread of diabetes mellitus will affect the population in relation to the demographic characteristics used in the study, namely; age, gender, and household income.
Researchers Findings
The researchers after adjusting the prevalence rates of diabetes for age and sex would decrease. Cases that were reported early in the diagnosis were attended to at early ages giving the people suffering from diabetes mellitus a longer time to live rather than die off. Most of these were females, therefore, the continued reporting helped in an increase in both males and females in the population leading to less cases of diabetes mellitus.
Odds ratio
The odds ratio showed that most people above 65 years showed that they are prone to diabetes mellitus as compared to other age groups (Wong et al., 2012). With the interpretation showing that the odds ratio of people aged above 65 years is higher, is shows that they are more prevalent to being diagnosed with the disease than all other age groups (Stephanie, 2014a). This clearly supports the alternative hypothesis that states, “There is a relationship between the rise in cases of diabetes mellitus in the Chinese population with an increase in age as well as a decrease in household income.”
Impact of limitations
The study showed firstly the limitation that the researchers relied on self-reported information to ascertain the prevalence of diabetes, and recent studies in China suggested three out of four diabetes patients were undiagnosed. This proves that most people would not come forward to present appropriate data that would be used for the study. With a sample size of at least 120,000 people, the information collected would not help in making assumptions of a Chinese population that was over 1 billion people in population. The results of the study would be insignificant in making assumptions and conclusion over such a big population.
Secondly, the study poses a limitation citing that it deploys stratified random sampling. The disadvantage of using this a form of sampling is that stratified random sampling is not reliable for all studies in question in research. With members of an investigation being in more demographics, some studies prove insignificant in using this sampling system. Some specific studies may overlap with some found in two or more different subgroups of a particular population under investigation for a study by researchers. This interprets that there would be more causes to the increase of diabetes mellitus as a prevalent disease over the age. Therefore, the null hypothesis that states, “Over the years between 2001 and 2008, age does not affect the rising cases of diabetes mellitus in the Chinese population” is proved wrong. With other factors affecting such an age group of people over 65 years of age, diabetes mellitus may be prevalent due to such factors. These factors may include a change in diet, loss of taste sensation due to old age, therefore, this age group will opt for sweeter things. Additionally, old age comes with cases of body complications that may lead to the increase in cases of diabetes mellitus in such an age group.
References
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