Dietary pattern transitions, and the associations with BMI, waist circumference, weight and hypertension in a 7-year follow-up among the older Chinese population: a longitudinal study

The present 7-year longitudinal study shows that over time, older people’s diet has shifted towards the modern dietary pattern, and people with higher education level, and individuals living in the high urbanization level were more likely to have more modern diet. We found this change over time is consistent with secular trend, regardless of age, and contrary to the exception that people’s diets became more traditional as their age. In addition, the modern dietary pattern was associated with an increase in BMI, weight and WC, whereas the traditional dietary pattern led to a decrease in BMI, weight and WC. In this analysis we used the data from one survey to determine the dietary patterns as it was our intention to hold the definition of a traditional diet constant over time.

From 2004 to 2011, BMI and Wt were slightly decreasing over the years. This is mainly due to ageing being associated with a change in body composition, such as reduced amount of lean body mass [5]. Loss of muscle and thus strength contributes to functional impairment that can further developing in sarcopenia among older population [17]. Additionally, BMI can be affected in the older population as they tend to shrink with age, with loss of bone mass or density being the main reason for weight loss [18]. WC increased with age, from 82.9 cm in 2004 and 84.3 cm in 2011 (p for trend <0.001). As the BMI did not change much for older population, while WC largely increased over the years, this may suggest that BMI is an inferior predictor for NCDs. There is strong emerging evidence that WHO cut-offs for BMI may not be appropriate in increasing age [19, 20]. By meta-analysis of 32 longitudinal studies, Winter et al. shows that older people (≥65 years) who stand at the lower end of the recommended BMI range, have an increased the risk of mortality, while for those being overweight there was no increased risk of mortality [20]. Another longitudinal study shows that BMI was not associated with NCDs, while WC was strong associated with conditions, such as chronic heart failure [21] in the older population. The increased WC observed in the present study, needs to be addressed, as obesity in the abdominal area is associated with risk of metabolic syndrome [22] and higher mortality [20].

Our study found similar results to Batis et al. studies [23, 24] which also undertook longitudinal analysis of CHNS data, and found the increasing popularity of the modern dietary pattern. Our study adds to these by focussing on the older Chinese population, with our results showing that modern dietary pattern scores have dramatically increased during survey years among people aged 60 or above Reasons for this may lie in the dietary transitions due to shifts in the agricultural system and subsequent growth of modern retail and food service sectors in China in recent decades. These shifts in diet are towards increased refined carbohydrates, added sweeteners, edible oils, food from animal-sources, and decreased intake in legumes, fruit and vegetables [25]. Additionally, we found that this modern dietary pattern was preferred by people with higher education, and individuals living in the high urbanization level. Our previous study shows that older people with high education level have higher relative fat intakes (energy from fat) than those with illiterate, low or medium education levels; and people living in areas of high urbanization have higher relative fat intakes than those living in low- and medium urbanization levels [6]. Higher relative fat intake can partly explain the higher modern dietary pattern scores within these groups.

Some other studies have been conducted to assess changes in dietary pattern over time. Analysis of data from 33,840 women participating in the Swedish Mammography Cohort in 1987 and 1997, shows that changes in dietary patterns were significantly related to changes in BMI over nine years of follow up [26]. By using sequence analysis of 3418 participants at baseline in Framingham Heart Study, Pachucki [27] shows that adults with unhealthful trajectory are 1.79 times more likely to be overweight, and 2.4 times more likely to be obese. These results are consistent with our study, finding the strong associations between favourable body composition and traditional diet (health diet), compared with an increase in BMI, WC and Wt with modern diet (unhealthy diet).

The present study confirms our previous cross-sectional findings of a relationships between dietary patterns and obesity [3]. The traditional diet with its main components of rice, pork, fish and vegetables contributes to the inverse association with BMI, WC and weight. This is opposed by the modern diet with main components being processed and fast foods and a positive association with BMI, WC and weight. Although there is still dispute about the role of a rice-based dietary pattern in preventing obesity in Asian countries [28‐30], we found a diet with a high proportion of rice and vegetables helps to prevent weight gain, large WC and obesity in China. Rice is a low-energy food [29] and the predominant component of the traditional dietary pattern, but contributes little to modern dietary pattern.

Interestingly, although the modern dietary pattern contains too much fat, which contributes to the positive association with BMI/WC, BMI of older Chinese decreasing with the length of time were followed. This suggests the modern dietary pattern is a key player in age-related loss of muscle and bone mass. The increase in WC for a modern dietary pattern is consistent with current knowledge. Fat is redistributed from subcutaneous to intra-abdominal visceral depots during and after middle age. In old age, fat is redistributed to bone marrow, muscle, liver, and other ectopic sites. Also, the percent of ingested fat that is stored in subcutaneous depots is lower in older than young people, and the abdominal circumference increases in the old age [31]. Further research is require to identify the specific components of the modern dietary pattern, which can lead to loss of muscle and bone mass. Although we did not find significant associations between dietary patterns and hypertension, we found BMI and WC are potential confounding or matching variables for hypertension.

The shift in dietary pattern over the years towards a modern diet is associated with rapid economic and social development in China. Older people have specific dietary needs and are at high risk of an unbalanced diet, which suggests that dietary guidelines should be developed for the older population. Although there is general advice for people aged 60 years or over [11, 32], age-specific guidelines for the older population is extremely important to encourage healthy eating in promoting healthy ageing, especially within the context of the aging Chinese population.

The strengths of the present study include the use of individual 24 h recall over consecutive 3 days. This method improves the accuracy of recall and hence analysis and results, and four time points allowing longitudinal analysis of associations. A weakness of this study is the large amount of missing data due to attrition. For continuous outcomes we analysed the data using LMMs, which are valid under the assumption that, conditional on the covariates included in the model, the data are missing at random. For the dichotomous outcome of hypertension we used the generalised estimating equation framework, which are valid under the assumption that the data are missing completely at random, conditional on the covariates included in the models. In our most comprehensive models we included the covariates of age, urbanization, gender, marital status, work status, education level, smoking, physical activity, traditional dietary pattern and energy intake, known diabetes, myocardial infarction and stoke. However, it’s possible and even probable that after taking these variables into account there are unmeasured characteristics which predict missingness and hence the data would be considered missing not at random. We could have used multiple imputations to impute the missing data under some assumptions about the missing data but the likelihood of getting the appropriate mechanism correct is low, and therefore we do not believe that it would have added anything to the analysis. With participants lost to follow-up more likely to be from the high risk group (Additional files 1, 2 and 3, Fig. 2), the GEE may underestimate the associations between dietary patterns and BMI, Wt, WC and hypertension. However, when we fit a random effects logistic regression model to the hypertension outcome we get very similar p-values to those from the GEE, but we have chosen to report the results from the GEE in this paper because we believe the population average interpretation is more appropriate in this circumstance.

The potential limitation is due to measurement error of food intake levels, residual confounding and the relatively short follow-up time. Some studies show that different types of rice result in different glycaemic responses, and their consumption may affect dietary management of obesity [33] (such as brown rice have beneficial role than white rice), we are not able to distinguish the effects of each type of rice as the consumption of brown rice by the study participants is low.