Background: Cancer diagnosis may be a cue for health behavior change. Previous research that assessed the impact of a cancer diagnosis on multiple health behavior (MHB) change is limited by small sample size, cross‐sectional study design, and a focus on individual rather than multiple behaviors. This study investigated the impact of a cancer diagnosis on compliance with MHB recommendations.Methods: Data from Australian Longitudinal Study on Women's Health (ALSWH) were utilized. Compliance with MHB was assessed by cancer survivorship period; 0‐3 years pre‐diagnosis, 0‐3 years postdiagnosis, 4‐12 years postdiagnosis, and compared to controls. A MHB score based on the WCRF/AICR guidelines was calculated for six behaviors (physical activity, smoking, alcohol, BMI, fruit, and vegetable intake); scores ranged from 0 to 6, with a higher score indicating higher compliance. Generalized estimating equation (GEE) was used for statistical analysis.Results: Participants comprised 7585 women from the 2001 ALSWH survey, of whom 2285 developed cancer during 15 years of follow‐up. Compared to controls, the mean MHB score was slightly lower (Mean Difference (MD) = −0.015, P > .05) in survivors pre‐diagnosis, after adjusting for confounders; however, the compliance score increased during postdiagnosis, with the mean difference score being significantly higher in recent survivors (0‐3 years post diagnosis; MD = 0.055, P < .01). Likewise, within cancer survivors, the mean compliance score significantly increased 0‐3 years postdiagnosis (MD = 0.07, P < .05) compared to pre‐diagnosis, but this significant improvement was not maintained over the longer term (MD = 0.037, P > .05).Conclusion: In this sample, survivors had higher MHB score than controls. A cancer diagnosis may provide a teachable moment for health behavior change in the period immediately following diagnosis, but this effect was not sustained during longer‐term survivorship.

Distilling the complexity of overall diet into a simple measure or summative score by data reduction methods has become a common practice in nutritional epidemiology. Recent reviews on diet quality indices (DQI) have highlighted the importance of sound construction criteria and validation. The aim of this current review was to identify and critically appraise all DQI used within Australian and New Zealand adult populations. Twenty-five existing DQI were identified by electronic searching in Medline and hand searching of reference lists. DQI were constructed based on the respective national dietary guidelines and condition-specific recommendations. For preferable features of DQI, six captured the dimensions of adequacy, moderation and balance; five had a nested structure; 12 consisted of foods, food groups and nutrients; 11 used metric scoring systems and most of those with metric scales used normative cutoff points. Food frequency questionnaires, either alone or with other methods, were the most common dietary assessment method used in 20 DQI. For evaluation of DQI, construct validity and relative validity are reported. Based on our critical appraisal, Dietary Guideline Index (DGI), Dietary Guideline Index-2013 (DGI-2013), Total Diet Score (TDS), Healthy Eating Index for Australian Adults-2013 (HEIFA-2013), and Aussie-Diet Quality Index (Aussie-DQI) were the preferred DQI used in Australian adults according to dimension, indicator selection, scoring criteria and evaluation. Further work is needed to enhance the construction of all Australian and New Zealand DQI, especially in terms of dimension and structure, for alignment with recommended construction criteria.

Diet quality indices (DQIs) can be useful predictors of diet–disease relationships, including non-communicable disease (NCD) multimorbidity. We aimed to investigate whether overall diet quality (DQ) predicted NCD, multimorbidity, and all-cause mortality. Women from the 1945–51 cohort of the Australia Longitudinal Study on Women’s Health (ALSWH) were included if they: responded to S3 in 2001 and at least one survey between 2004 (S4) and 2016 (S8), and had no NCD history and complete dietary data at S3. DQ was summarized by the Healthy Eating Index for Australian Adults-2013 (HEIFA-2013), Mediterranean Diet Score (MDS), and Alternative Healthy Eating Index-2010 (AHEI-2010). Outcomes included each NCD (diabetes mellitus (DM), coronary heart disease (CHD), hypertension (HT), asthma, cancer (except skin cancer), depression and/or anxiety) independently, multimorbidity, and all-cause mortality. Repeated multivariate logistic regressions were used to test associations between DQIs and NCD outcomes across the 15 years of follow-up. The mean (±sd) of DQIs of participants (n = 5350) were 57.15 ± 8.16 (HEIFA-2013); 4.35 ± 1.75 (MDS), and 56.01 ± 10.32 (AHEI-2010). Multivariate regressions indicated that women reporting the highest quintile of AHEI-2010 had lower odds of DM (42–56% (S5–S8)), HT (26% (S8)), asthma (35–37% (S7, S8)), and multimorbidity (30–35% (S7, S8)). The highest quintile of HEIFA-2013 and MDS had lower odds of HT (26–35% (S7, S8); 24–27% (S6–S8), respectively) and depression and/or anxiety (30% (S6): 30–34% (S7, S8)). Our findings support evidence that DQ is an important predictor of some NCDs and a target for prevention in middle-aged women.

Objectives and importance of study: The purpose of this study was to illustrate how qualitative free-text comments, collected within the context of a health survey, represent a rich data source for understanding specific phenomena. Study type: Work conducted with data from the Australian Longitudinal Study on Women’s Health (ALSWH) was used to demonstrate the breadth and depth of qualitative information that can be collected. The ALSWH has been collecting data on women’s health since 1996, and represents a unique opportunity for understanding lived experiences across the lifecourse. Methods: A multiple case study design was used to demonstrate the techniques that researchers have used to manage free-text qualitative comments collected by the ALSWH. Results and conclusions: Eleven projects conducted using free-text comments are discussed according to the method of analysis. These methods include coding (both inductively and deductively), longitudinal analyses and software-based analyses. This work shows that free-text comments are a data resource in their own right, and have the potential to provide rich and valuable information about a wide variety of topics.

Objective: The aim of the present study was to examine non-communicable disease (NCD) policy formation and implementation in Indonesia. Methods: Interviews were conducted with 13 Indonesian health policy workers. The processes and issues relating to NCD policy formation were mapped, exploring the interactions between policy makers, technical/implementation bodies, alliances across various levels and the mobilisation of non-policy actors. Results: Problems in NCD policy formation include insufficient political interest in NCD control, disconnected policies and difficulty in multisectoral coordination. These problems are well illustrated in relation to tobacco control, but also apply to other control efforts. Nevertheless, participants were optimistic that there are plentiful opportunities for improving NCD control policies given growing global attention to NCD, increases in the national health budget and the growing body of Indonesia-relevant NCD-related research. Conclusion: Indonesia’s success in the creation and implementation of NCD policy will be dependent on high-level governmental leadership, including support from the President, the Health Minister and coordinating ministries. What is known about the topic?: The burden of NCD in Indonesia has increased gradually. Nationally, NCD-related mortality accounted for 65% of deaths in 2010. Indonesia is also a country with the highest burden of tobacco smoking in the world. However, the government has not instituted sufficient policy action to tackle NCDs, including tobacco control. What does this paper add?: This paper deepens our understanding of current NCD control policy formation in Indonesia, including the possible underlying reason why Indonesia has weak tobacco control policies. It describes the gaps in the current policies, the actors involved in policy formation, the challenges in policy formation and implementation and potential opportunities for improving NCD control. What are the implications for practitioners?: An effective NCD control program requires strong collaboration, including between government and health professionals. Health professionals can actively engage in policy formation, for example through knowledge production.

Lifestyle behaviours have an important role in preventing cancer, reducing treatment side effects, and improving survival and quality of life for cancer survivors. This study investigated adherence to multiple lifestyle behaviours among women with and without a cancer history. From the Australian Longitudinal Study on Women’s Health (ALSWH) surveys, 2407 cancer survivors and 3896 controls (cancer free population) were identified. Based on the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations, adherence to six health behaviours (smoking, physical activity, fruit and vegetable intake, alcohol consumption, sugary drink intake, and Body Mass Index [BMI]) were assessed. Overall adherence was low, and there were no differences between survivors and controls on adherence to any of the six individual health behaviours. However, both recent and long-term cancer survivors were more likely than controls to adhere to multiple health behaviours (p < 0.05). When participants with melanoma or non-melanoma skin cancer were excluded, adherence was less likely (but not significant) in the cancer group than controls. Higher education (p < 0.01), being married (p < 0.01), and lower comorbidity of chronic illnesses (p < 0.01) were significantly associated with adherence to multiple lifestyle behaviours. Overall, the findings suggest that a cancer diagnosis may result in increased compliance with multiple health behaviour guidelines.