225 resultados para Maternal demographic characteristics
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Objective: Food insecurity may be associated with a number of adverse health and social outcomes however our knowledge of its public health significance in Australia has been limited by use of a single-item measure in the Australian National Health Surveys (NHS) and, more recently, the exclusion of food security items from these surveys. The current study compares prevalence estimates of food insecurity in disadvantaged urban areas of Brisbane using the one-item NHS measure with three adaptations of the United States Department of Agriculture Food Security Survey Module (USDA-FSSM). Design: Data were collected by postal survey (n= 505, 53% response). Food security status was ascertained by the measure used in the NHS, and the 6-, 10- and 18-item versions of the USDA-FSSM. Demographic characteristics of the sample, prevalence estimates of food insecurity and different levels of food insecurity estimated by each tool were determined. Setting: Disadvantaged suburbs of Brisbane city, Australia, 2009. Subjects: Individuals aged ≥ 18 years. Results: Food insecurity was prevalent in socioeconomically-disadvantaged urban areas, estimated as 19.5% using the single-item NHS measure. This was significantly less than the 24.6% (P <0.01), 22.0% (P = 0.01) and 21.3% (P = 0.03) identified using the 18-item, 10-item and 6-item versions of the USDA-FSSM, respectively. The proportion of the sample reporting more severe levels of food insecurity were 10.7%, 10% and 8.6% for the 18-, 10- and 6-item USDA measures respectively, however this degree of food insecurity could not be ascertained using the NHS measure. Conclusions: The measure of food insecurity employed in the NHS may underestimate its prevalence and public health significance. Future monitoring and surveillance efforts should seek to employ a more accurate measure.
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BACKGROUND/OBJECTIVES: To describe the diet quality of a national sample of Australian women with a recent history of gestational diabetes mellitus (GDM) and determine factors associated with adherence to national dietary recommendations. SUBJECTS/METHODS: A postpartum lifestyle survey with 1499 Australian women diagnosed with GDM p3 years previously. Diet quality was measured using the Australian recommended food score (ARFS) and weighted by demographic and diabetes management characteristics. Multinominal logistic regression analysis was used to determine the association between diet quality and demographic characteristics, health seeking behaviours and diabetes-related risk factors. RESULTS: Mean (±s.d.) ARFS was 30.9±8.1 from a possible maximum score of 74. Subscale component scores demonstrated that the nuts/legumes, grains and fruits were the most poorly scored. Factors associated with being in the highest compared with the lowest ARFS quintile included age (odds ratio (OR) 5-year increase=1.40; 95% (confidence interval) CI:1.16–1.68), tertiary education (OR=2.19; 95% CI:1.52–3.17), speaking only English (OR=1.92; 95% CI:1.19–3.08), being sufficiently physically active (OR=2.11; 95% CI:1.46–3.05), returning for postpartum blood glucose testing (OR=1.75; 95% CI:1.23–2.50) and receiving riskreduction advice from a health professional (OR=1.80; 95% CI:1.24–2.60). CONCLUSIONS: Despite an increased risk of type 2 diabetes, women in this study had an overall poor diet quality as measured by the ARFS. Women with GDM should be targeted for interventions aimed at achieving a postpartum diet consistent with the guidelines for chronic disease prevention. Encouraging women to return for follow-up and providing risk reduction advice may be positive initial steps to improve diet quality, but additional strategies need to be identified.
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This project advances current understanding of intra-urban rail passengers and their travel experiences in order to help rail industry leaders tailor policy approaches to fit specific, relevant segments of their target population. Using a Q sorting technique and cluster analysis, our preliminary research identified five perspectives occurring in a small sample of rail passengers, who varied in their frequency and location of rail travel as well as certain socio-demographic characteristics. Revealed perspectives (named to capture the gist of their content) included: ‘Rail Travel is About the Destination, Not the Journey’; ‘Despite Challenges, Public Transport is Still the Best Option’; ‘Rail Travel is Fine’; ‘Rail Travel? So Far, So Good’; and ‘Bad Taste for Rail Travel’. This paper discusses each of the perspectives in detail, and considers them in terms of tailored policy implications. An overarching finding from this study is that improving railway travel ‘access’ requires attention to physical, psychological, financial, and social facets of accessibility. For example, designing waiting areas to be more socially functional and comfortable has the potential to increase ridership by addressing social forms of access, decreasing perceived wait times, and making time at the station feel like time well spent. Even at this preliminary stage, the Q sorting technique promises to provide a valuable, holistic albeit fine-grained analysis of passenger attitudes and experiences that will assist industry efforts to increase ridership.
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A major priority for cancer control agencies is to reduce geographical inequalities in cancer outcomes. While the poorer breast cancer survival among socioeconomically disadvantaged women is well established, few studies have looked at the independent contribution that area- and individual-level factors make to breast cancer survival. Here we examine relationships between geographic remoteness, area-level socioeconomic disadvantage and breast cancer survival after adjustment for patients’ socio- demographic characteristics and stage at diagnosis. Multilevel logistic regression and Markov chain Monte Carlo simulation were used to analyze 18 568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30 to 70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas in Queensland, Australia. Independent of individual-level factors, area-level disadvantage was associated with breast-cancer survival (p=0.032). Compared to women in the least disadvantaged quintile (Quintile 5), women diagnosed while resident in one of the remaining four quintiles had significantly worse survival (OR 1.23, 1.27, 1.30, 1.37 for Quintiles 4, 3, 2 and 1 respectively).) Geographic remoteness was not related to lower survival after multivariable adjustment. There was no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual level, Indigenous status, blue collar occupations and advanced disease were important predictors of poorer survival. A woman’s survival after a diagnosis of breast cancer depends on the socio-economic characteristics of the area where she lives, independently of her individual-level characteristics. It is crucial that the underlying reasons for these inequalities be identified to appropriately target policies, resources and effective intervention strategies.
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Heatwaves are associated with significant health risks particularly among vulnerable groups. To minimize these risks, heat warning systems have been implemented. The question therefore is how effective these systems are in saving lives and reducing heat-related harm. We systematically searched and reviewed 15 studies which examined this. Six studies asserted that fewer people died of excessive heat after the implementation of heat warning systems. Demand for ambulance decreased following the implementation of these systems. One study also estimated the costs of running heat warning systems at US$210,000 compared to the US$468 million benefits of saving 117 lives. The remaining eight studies investigated people?s response to heat warning systems and taking appropriate actions against heat harms. Perceived threat of heat dangers emerged as the main factor related to heeding the warnings and taking proper actions. However, barriers, such as costs of running air-conditioners, were of significant concern, particularly to the poor. The weight of the evidence suggests that heat warning systems are effective in reducing mortality and, potentially, morbidity. However, their effectiveness may be mediated by cognitive, emotive and socio-demographic characteristics. More research is urgently required into the cost-effectiveness of heat warning systems? measures and improving the utilization of the services.
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OBJECTIVE There has been a dramatic increase in vitamin D testing in Australia in recent years, prompting calls for targeted testing. We sought to develop a model to identify people most at risk of vitamin D deficiency. DESIGN AND PARTICIPANTS This is a cross-sectional study of 644 60- to 84-year-old participants, 95% of whom were Caucasian, who took part in a pilot randomized controlled trial of vitamin D supplementation. MEASUREMENTS Baseline 25(OH)D was measured using the Diasorin Liaison platform. Vitamin D insufficiency and deficiency were defined using 50 and 25 nmol/l as cut-points, respectively. A questionnaire was used to obtain information on demographic characteristics and lifestyle factors. We used multivariate logistic regression to predict low vitamin D and calculated the net benefit of using the model compared with 'test-all' and 'test-none' strategies. RESULTS The mean serum 25(OH)D was 42 (SD 14) nmol/1. Seventy-five per cent of participants were vitamin D insufficient and 10% deficient. Serum 25(OH)D was positively correlated with time outdoors, physical activity, vitamin D intake and ambient UVR, and inversely correlated with age, BMI and poor self-reported health status. These predictors explained approximately 21% of the variance in serum 25(OH)D. The area under the ROC curve predicting vitamin D deficiency was 0·82. Net benefit for the prediction model was higher than that for the 'test-all' strategy at all probability thresholds and higher than the 'test-none' strategy for probabilities up to 60%. CONCLUSION Our model could predict vitamin D deficiency with reasonable accuracy, but it needs to be validated in other populations before being implemented.
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Background: Fatigue is a distressing symptom experienced by approximately 74-88% of patients with advanced cancer. Although there have been advances in managing fatigue with the use of a range of pharmacologic and non-pharmacologic strategies, fatigue is not well-managed in patients with advanced cancer. Objectives: For patients with advanced cancer, the aims of the study were to examine the self-management (SM) behaviours associated with fatigue; the perceived effectiveness of these SM behaviours, and the socio-demographic and clinical factors influencing the effectiveness of these SM behaviours. Methodology: A prospective longitudinal study was undertaken with 152 patients with metastatic breast, lung, colorectal and prostate cancer experiencing fatigue (>3/10) over a two month period. SM behaviours associated with fatigue, medical/demographic characteristics, social support, depression, anxiety, self-efficacy and other symptoms were assessed. Results: Findings indicate that on most fatigue severity measures, levels of fatigue increased slightly over time. On average, participants used nine fatigue SM behaviours at each time point. Participants reported that the most effective SM behaviours were ‘pacing their activities during the day’, ‘planning activities to make the most of energy’, ‘taking short sleeps’, ‘doing things that distract them from their fatigue’, and ‘doing things to improve sleep at night’. Factors associated with the increased effectiveness of fatigue SM behaviours included higher self-efficacy, higher education level, lower levels of depressive symptoms, and lower functional status. These results can be used to inform the design of future interventions to support the use of effective fatigue SM behaviours in this population.
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In developed countries the relationship between socioeconomic position (SEP) and health is unequivocal. Those who are socioeconomically disadvantaged are known to experience higher morbidity and mortality from a range of chronic diet-related conditions compared to those of higher SEP. Socioeconomic inequalities in diet are well established. Compared to their more advantaged counterparts, those of low SEP are consistently found to consume diets less consistent with dietary guidelines (i.e. higher in fat, salt and sugar and lower in fibre, fruit and vegetables). Although the reasons for dietary inequalities remain unclear, understanding how such differences arise is important for the development of strategies to reduce health inequalities. Both environmental (e.g. proximity of supermarkets, price, and availability of foods) and psychosocial (e.g. taste preference, nutrition knowledge) influences are proposed to account for inequalities in food choices. Although in the United States (US), United Kingdom (UK), and parts of Australia, environmental factors are associated with socioeconomic differences in food choices, these factors do not completely account for the observed inequalities. Internationally, this context has prompted calls for further exploration of the role of psychological and social factors in relation to inequalities in food choices. It is this task that forms the primary goal of this PhD research. In the small body of research examining the contribution of psychosocial factors to inequalities in food choices, studies have focussed on food cost concerns, nutrition knowledge or health concerns. These factors are generally found to be influential. However, since a range of psychosocial factors are known determinants of food choices in the general population, it is likely that a range of factors also contribute to inequalities in food choices. Identification of additional psychosocial factors of relevance to inequalities in food choices would provide new opportunities for health promotion, including the adaption of existing strategies. The methodological features of previous research have also hindered the advancement of knowledge in this area and a lack of qualitative studies has resulted in a dearth of descriptive information on this topic. This PhD investigation extends previous research by assessing a range of psychosocial factors in relation to inequalities in food choices using both quantitative and qualitative techniques. Secondary data analyses were undertaken using data obtained from two Brisbane-based studies, the Brisbane Food Study (N=1003, conducted in 2000), and the Sixty Families Study (N=60, conducted in 1998). Both studies involved main household food purchasers completing an interviewer-administered survey within their own home. Data pertaining to food-purchasing, and psychosocial, socioeconomic and demographic characteristics were collected in each study. The mutual goals of both the qualitative and quantitative phases of this investigation were to assess socioeconomic differences in food purchasing and to identify psychosocial factors relevant to any observed differences. The quantitative methods then additionally considered whether the associations examined differed according to the socioeconomic indicator used (i.e. income or education). The qualitative analyses made a unique contribution to this project by generating detailed descriptions of socioeconomic differences in psychosocial factors. Those with lower levels of income and education were found to make food purchasing choices less consistent with dietary guidelines compared to those of high SEP. The psychosocial factors identified as relevant to food-purchasing inequalities were: taste preferences, health concerns, health beliefs, nutrition knowledge, nutrition concerns, weight concerns, nutrition label use, and several other values and beliefs unique to particular socioeconomic groups. Factors more tenuously or inconsistently related to socioeconomic differences in food purchasing were cost concerns, and perceived adequacy of the family diet. Evidence was displayed in both the quantitative and qualitative analyses to suggest that psychosocial factors contribute to inequalities in food purchasing in a collective manner. The quantitative analyses revealed that considerable overlap in the socioeconomic variation in food purchasing was accounted for by key psychosocial factors of importance, including taste preference, nutrition concerns, nutrition knowledge, and health concerns. Consistent with these findings, the qualitative transcripts demonstrated the interplay between such influential psychosocial factors in determining food-purchasing choices. The qualitative analyses found socioeconomic differences in the prioritisation of psychosocial factors in relation to food choices. This is suggestive of complex cultural factors that distinguish advantaged and disadvantaged groups and result in socioeconomically distinct schemas related to health and food choices. Compared to those of high SEP, those of lower SEP were less likely to indicate that health concerns, nutrition concerns, or food labels influenced food choices, and exhibited lower levels of nutrition knowledge. In the absence of health or nutrition-related concerns, taste preferences tended to dominate the food purchasing choices of those of low SEP. Overall, while cost concerns did not appear to be a main determinant of socioeconomic differences in food purchasing, this factor had a dominant influence on the food choices of some of the most disadvantaged respondents included in this research. The findings of this study have several implications for health promotion. The integrated operation of psychosocial factors on food purchasing inequalities indicates that multiple psychosocial factors may be appropriate to target in health promotion. It also seems possible that the inter-relatedness of psychosocial factors would allow health promotion targeting a single psychosocial factor to have a flow-on affect in terms of altering other influential psychosocial factors. This research also suggests that current mass marketing approaches to health promotion may not be effective across all socioeconomic groups due to differences in the priorities and main factors of influence in food purchasing decisions across groups. In addition to the practical recommendations for health promotion, this investigation, through the critique of previous research, and through the substantive study findings, has highlighted important methodological considerations for future research. Of particular note are the recommendations pertaining to the selection of socioeconomic indicators, measurement of relevant constructs, consideration of confounders, and development of an analytical approach. Addressing inequalities in health has been noted as a main objective by many health authorities and governments internationally. It is envisaged that the substantive and methodological findings of this thesis will make a useful contribution towards this important goal.
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Aims and objectives. To examine Chinese cancer patients’ fatigue self-management, including the types of self-management behaviours used, their confidence in using these behaviours, the degree of relief obtained and the factors associated with patients’ use of fatigue self-management behaviours. Background. Fatigue places significant burden on patients with cancer undergoing chemotherapy. While some studies have explored fatigue self-management in Western settings, very few studies have explored self-management behaviours in China. Design. Cross-sectional self- and/or interviewer-administered survey. Methods. A total of 271 participants with self-reported fatigue in the past week were recruited from a specialist cancer hospital in south-east China. Participants completed measures assessing the use of fatigue self-management behaviours, corresponding self-efficacy, perceived relief levels plus items assessing demographic characteristics, fatigue experiences, distress and social support. Results. A mean of 4_94 (_2_07; range 1–10) fatigue self-management behaviours was reported. Most behaviours were rated as providing moderate relief and were implemented with moderate self-efficacy. Regression analyses identified that having more support from one’s neighbourhood and better functional status predicted the use of a greater number of self-management behaviours. Separate regression analyses identified that greater neighbourhood support predicted greater relief from ‘activity enhancement behaviours’ and that better functional status predicted greater relief from ‘rest and sleep behaviours’. Higher self-efficacy scores predicted greater relief from corresponding behaviours. Conclusions. A range of fatigue self-management behaviours were initiated by Chinese patients with cancer. Individual, condition and environmental factors were found to influence engagement in and relief from fatigue self-managementbehaviours. Relevance to clinical practice. Findings highlight the need for nurses to explore patients’ use of fatigue self-management behaviours and the effectiveness of these behaviours in reducing fatigue. Interventions that improve patients’ self-efficacy and neighbourhood supports have the potential to improve outcomes from fatigue self-management behaviours.
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Transport related injury is a leading cause of death and disability for adolescents and represents a substantial burden on public health and the community as a whole. Adolescents appear to have a growing risk of harm due to the co-existence of increasing alcohol use and engagement in risky transport behaviours. Understanding more about the development and stability of these behaviours by young adolescents over time could be beneficial in targeting transport injury prevention interventions for high-risk adolescents. In Australia alcohol use begins to increase significantly through the early and middle adolescent years even though the majority of these young people are still in school. Aim This paper reports on changes over a six month period in alcohol use, anger management experiences and transport risk taking behaviours including riding a bicycle without a helmet and under-age driving for high-risk adolescents and non high-risk early adolescents. Year 9 students (N=1,005) from 20 schools in Queensland, Australia completed a baseline survey in the first half of 2012 and at a six month follow up. Respondents at both times were asked about their engagement in risk taking behaviours measured by Mak’s adolescent delinquency scale, which included five transport related items. They were also asked to rate their alcohol use for the preceding three month period. The stability of these risk taking indicators was measured by comparing baseline results with the six month follow up. Results High-risk adolescents were more likely to report change in their alcohol use and transport behaviours when compared with non high-risk adolescents over a six month period. There were no significant changes in control of anger for either group. Demographic characteristics were not shown to have any significant effect on the stability of risk indicators for high-risk adolescents and non high-risk adolescents. Differences were found in the stability of risk taking indicators for high-risk adolescents and non high-risk adolescents. The findings of this paper have implications in targeting transport risk behaviour change interventions to meet the needs of high-risk adolescents.
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Objective: To examine the extent to which socio-demographics, modifiable lifestyle, and physical health status influence the mental health of post-menopausal Australian women. Methods: Cross-sectional data on health status, chronic disease and modifiable lifestyle factors were collected from a random cross-section of 340 women aged 60-70 years, residing in Queensland, Australia. Structural equation modelling (SEM) was used to measure the effect of a range of socio-demographic characteristics, modifiable lifestyle factors, and health markers (self-reported physical health, history of chronic illness) on the latent construct of mental health status. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) which examined and Center for Epidemiologic Studies Depression Scale (CES-D). Results: The model was a good fit for the data (χ2=4.582, df=3, p=0.205) suggesting that mental health is negatively correlated with sleep disturbance (β = -0.612, p <0.001), and a history of depression (β = -0.141, p = 0.024).While mental health was associated with poor sleep, it was not correlated with most lifestyle factors (BMI, alcohol consumption, or cigarette smoking) or socio-demographics like age, income or employment category and they were removed from the final model. Conclusion: Research suggests that it is important to engage in a range of health promoting behaviours to preserve good health. We found that predictors of current mental health status included sleep disturbance, and past mental health problems, while socio-demographics and modifiable lifestyle had little impact. It may be however, that these factors influenced other variables associated with the mental health of post-menopausal women, and these relationships warrant further investigation.
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Background: Sleep disturbance in midlife women has been studied extensively, although less is known about sleep after menopause. This study examined the relative impact of socio-demographics, modifiable lifestyle factors, and health status on sleep disturbance in post-menopausal women from Queensland, Australia. Methods: The longitudinal Healthy Aging of Women (HOW) study examines health-related quality of life (HRQOL measured by SF-12©), chronic illness, modifiable lifestyle factors such as physical activity, alcohol consumption, smoking, and sleep disturbance (General Sleep Disturbance Scale, GSDS ≥ 43 represent poor sleep) in midlife and older women from low and high socio-economic, rural and urban areas of South-East Queensland, Australia. This paper presents cross-sectional data from the 322 women, aged 60-70 years, participating in the HOW study in 2011. Results: For women in this study, sleep disturbance was relatively common, with 23% (n = 83) reporting poor sleeping (GSDS ≥ 43). Sleep disturbance scores were strongly correlated with being unemployed or on a disability support pension (β = 18.69, P < 0.01), sedentary lifestyle (β = 23.84, P < 0.01), and lower mental (β = -0.60, P <0.01) and physical health-related quality of life scores (β = -0.32, P = 0.01), and these variables explained almost one third of variance in sleep disturbance scores (ηρ² = 29%). Conclusions: Multivariable analysis revealed that sleep disturbance was correlated with physical and mental health-related quality of life, disability, and sedentary lifestyle, but not other lifestyle and socio-demographic characteristics. It may be however, that modifiable lifestyle factors may indirectly impact on sleep by influencing health status.
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This study aimed to investigate drink driving in a sample of general drivers and convicted drunk driving offenders in Guangzhou, China. The study also aimed to explore some potential factors that impact on alcohol-related driving behaviour. Samples of 406 general drivers and 101 drunk driving offenders were recruited between May and October 2012. A survey was used to collect information about demographic characteristics, knowledge, attitudes and practices related to drink driving. The Alcohol Use Disorders Identification Test (AUDIT) was used to assess possible drinking problems. The average age reported for starting to drink alcohol for both groups of participants was around 19 years old. The mean AUDIT score of general drivers was 7.4 (SD = 5.4) representing a low level of alcohol problems, and for convicted drunk driving offenders was 11.1 (SD = 5.9) representing a medium level of alcohol problems (significant difference between means, t = 5.75, p < 0.001). AUDIT scores indicated that a substantial proportion (65%) of the offenders had medium to high levels of alcohol use disorders, compared with 38.5% among general drivers. Offenders who knew the drunk driving legal limit had a lower AUDIT score (M = 9.8, SD = 5.16) than those who did not know it (M = 12.2, SD = 6.257, t = -1.987. p = 0.05). In addition, offenders who were novice drivers (licensed less than 2 years) had a higher AUDIT score (M = 16.4, SD = 7.6) than the other three driver experience categories used.
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Physical activity (PA) has many beneficial physical and mental health effects. Physical inactivity is considered the fourth leading risk factor for global mortality. At present there are no systematic reviews on PA patterns among South Asian adults residing in the region. The present study aims to systematically evaluate studies on PA patterns in South Asian countries. A five-staged comprehensive search of the literature was conducted in Medline, Web of Science and SciVerse Scopus using keywords ‘Exercise’, ‘Walking’, ‘Physical activity’, ‘Inactivity’, ‘Physical Activity Questionnaire’, ‘International Physical Activity Questionnaire’, ‘IPAQ’, ‘Global Physical Activity Questionnaire’ and ‘GPAQ’, combined with individual country names. The search was restricted to English language articles conducted in humans and published before 31st December 2012. To obtain additional data a manual search of the reference lists of articles was performed. Data were also retrieved from the search of relevant web sites and online resources. The total number of hits obtained from the initial search was 1,771. The total number of research articles included in the present review is eleven (India-8, Sri Lanka-2, Pakistan-1). In addition, eleven country reports (Nepal-3, Bangladesh-2, India-2, Sri Lanka-2, Bhutan-1, Maldives-1) of World Health Organization STEPS survey from the South-Asian countries were retrieved online. In the research articles the overall prevalence of inactivity was as follows; India (18.5%-88.4%), Pakistan (60.1%) and Sri Lanka (11.0%-31.8%). STEPS survey reports were available from all countries except Pakistan. Overall in majority of STEPS surveys females were more inactive compared to males. Furthermore, leisure related inactivity was >75% in studies reporting inactivity in this domain and people were more active in transport domain when compared with the other domains. In conclusion, our results show that there is a wide variation in the prevalence of physical inactivity among South-Asian adults within and between countries. Furthermore, physical inactivity in South Asian adults was associated with several socio-demographic characteristics. Majority of South Asian adults were inactive during their leisure time. These Factors need to be considered when planning future interventions and research aimed at improving PA in the region.
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Traditionally, infectious diseases and under-nutrition have been considered major health problems in Sri Lanka with little attention paid to obesity and associated non-communicable diseases (NCDs). However, the recent Sri Lanka Diabetes and Cardiovascular Study (SLDCS) reported the epidemic level of obesity, diabetes and metabolic syndrome. Moreover, obesity-associated NCDs is the leading cause of death in Sri Lanka and there is an exponential increase in hospitalization due to NCDs adversely affecting the development of the country. Despite Sri Lanka having a very high prevalence of NCDs and associated mortality, little is known about the causative factors for this burden. It is widely believed that the global NCD epidemic is associated with recent lifestyle changes, especially dietary factors. In the absence of sufficient data on dietary habits in Sri Lanka, successful interventions to manage these serious health issues would not be possible. In view of the current situation the dietary survey was undertaken to assess the intakes of energy, macro-nutrients and selected other nutrients with respect to socio demographic characteristics and the nutritional status of Sri Lankan adults especially focusing on obesity. Another aim of this study was to develop and validate a culturally specific food frequency questionnaire (FFQ) to assess dietary risk factors of NCDs in Sri Lankan adults. Data were collected from a subset of the national SLDCS using a multi-stage, stratified, random sampling procedure (n=500). However, data collection in the SLDCS was affected by the prevailing civil war which resulted in no data being collected from Northern and Eastern provinces. To obtain a nationally representative sample, additional subjects (n=100) were later recruited from the two provinces using similar selection criteria. Ethical Approval for this study was obtained from the Ethical Review Committee, Faculty of Medicine, University of Colombo, Sri Lanka and informed consent was obtained from the subjects before data were collected. Dietary data were obtained using the 24-h Dietary Recall (24HDR) method. Subjects were asked to recall all foods and beverages, consumed over the previous 24-hour period. Respondents were probed for the types of foods and food preparation methods. For the FFQ validation study, a 7-day weight diet record (7-d WDR) was used as the reference method. All foods recorded in the 24 HDR were converted into grams and then intake of energy and nutrients were analysed using NutriSurvey 2007 (EBISpro, Germany) which was modified for Sri Lankan food recipes. Socio-demographic details and body weight perception were collected from interviewer-administrated questionnaire. BMI was calculated and overweight (BMI ≥23 kg.m-2), obesity (BMI ≥25 kg.m-2) and abdominal obesity (Men: WC ≥ 90 cm; Women: WC ≥ 80 cm) were categorized according to Asia-pacific anthropometric cut-offs. The SPSS v. 16 for Windows and Minitab v10 were used for statistical analysis purposes. From a total of 600 eligible subjects, 491 (81.8%) participated of whom 34.5% (n=169) were males. Subjects were well distributed among different socio-economic parameters. A total of 312 different food items were recorded and nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Seventy-seven subjects completed (response rate = 65%) the FFQ and 7-day WDR. Estimated mean energy intake (SD) from FFQ (1794±398 kcal) and 7DWR (1698±333 kcal, P<0.001) was significantly different due to a significant overestimation of carbohydrate (~10 g/d, P<0.001) and to some extent fat (~5 g/d, NS). Significant positive correlations were found between the FFQ and 7DWR for energy (r = 0.39), carbohydrate (r = 0.47), protein (r = 0.26), fat (r =0.17) and dietary fiber (r = 0.32). Bland-Altman graphs indicated fairly good agreement between methods with no relationship between bias and average intake of each nutrient examined. The findings from the nutrition survey showed on average, Sri Lankan adults consumed over 14 portions of starch/d; moreover, males consumed 5 more portions of cereal than females. Sri Lankan adults consumed on average 3.56 portions of added sugars/d. Moreover, mean daily intake of fruit (0.43) and vegetable (1.73) portions was well below minimum dietary recommendations (fruits 2 portions/d; vegetables 3 portions/d). The total fruit and vegetable intake was 2.16 portions/d. Daily consumption of meat or alternatives was 1.75 portions and the sum of meat and pulses was 2.78 portions/d. Starchy foods were consumed by all participants and over 88% met the minimum daily recommendations. Importantly, nearly 70% of adults exceeded the maximum daily recommendation for starch (11portions/d) and a considerable proportion consumed larger numbers of starch servings daily, particularly men. More than 12% of men consumed over 25 starch servings/d. In contrast to their starch consumption, participants reported very low intakes of other food groups. Only 11.6%, 2.1% and 3.5% of adults consumed the minimum daily recommended servings of vegetables, fruits, and fruits and vegetables combined, respectively. Six out of ten adult Sri Lankans sampled did not consume any fruits. Milk and dairy consumption was extremely low; over a third of the population did not consume any dairy products and less than 1% of adults consumed 2 portions of dairy/d. A quarter of Sri Lankans did not report consumption of meat and pulses. Regarding protein consumption, 36.2% attained the minimum Sri Lankan recommendation for protein; and significantly more men than women achieved the recommendation of ≥3 servings of meat or alternatives daily (men 42.6%, women 32.8%; P<0.05). Over 70% of energy was derived from carbohydrates (Male:72.8±6.4%, Female:73.9±6.7%), followed by fat (Male:19.9±6.1%, Female:18.5±5.7%) and proteins (Male:10.6±2.1%, Female:10.9±5.6%). The average intake of dietary fiber was 21.3 g/day and 16.3 g/day for males and females, respectively. There was a significant difference in nutritional intake related to ethnicities, areas of residence, education levels and BMI categories. Similarly, dietary diversity was significantly associated with several socio-economic parameters among Sri Lankan adults. Adults with BMI ≥25 kg.m-2 and abdominally obese Sri Lankan adults had the highest diet diversity values. Age-adjusted prevalence (95% confidence interval) of overweight, obesity, and abdominal obesity among Sri Lankan adults were 17.1% (13.8-20.7), 28.8% (24.8-33.1), and 30.8% (26.8-35.2), respectively. Men, compared with women, were less overweight, 14.2% (9.4-20.5) versus 18.5% (14.4-23.3), P = 0.03, less obese, 21.0% (14.9-27.7) versus 32.7% (27.6-38.2), P < .05; and less abdominally obese, 11.9% (7.4-17.8) versus 40.6% (35.1-46.2), P < .05. Although, prevalence of obesity has reached to epidemic level body weight misperception was common among Sri Lankan adults. Two-thirds of overweight males and 44.7% of females considered themselves as in "about right weight". Over one third of both male and female obese subjects perceived themselves as "about right weight" or "underweight". Nearly 32% of centrally obese men and women perceived that their waist circumference is about right. People who perceived overweight or very overweight (n = 154) only 63.6% tried to lose their body weight (n = 98), and quarter of adults seek advices from professionals (n = 39). A number of important conclusions can be drawn from this research project. Firstly, the newly developed FFQ is an acceptable tool for assessing the nutrient intake of Sri Lankans and will assist proper categorization of individuals by dietary exposure. Secondly, a substantial proportion of the Sri Lankan population does not consume a varied and balanced diet, which is suggestive of a close association between the nutrition-related NCDs in the country and unhealthy eating habits. Moreover, dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Lastly, although obesity is a major health issue among Sri Lankan adults, body weight misperception was common among underweight, healthy weight, overweight, and obese adults in Sri Lanka. Over 2/3 of overweight and 1/3 of obese Sri Lankan adults believe that they are in "right weight" or "under-weight" categories.