Literature DB >> 29408921

The relationship between famine exposure during early life and body mass index in adulthood: A systematic review and meta-analysis.

Jielin Zhou1, Liangjian Zhang1, Peng Xuan1, Yong Fan1, Linsheng Yang1, Chunqiu Hu1, Qingli Bo1, Guoxiu Wang1, Jie Sheng1, Sufang Wang1.   

Abstract

BACKGROUND: Previous epidemiologic studies have reported famine exposure during early life association with overweight or obesity in adulthood, but a consistent perspective has not been established to date.
PURPOSE: To determine, by conducting a systematic review and meta-analysis, whether exposure to famine could increase body mass index (BMI) in adult or not, and assess the association between famine exposure and the risk of overweight or obesity.
METHODS: Published articles were systematically searched (until August, 2017) from PubMed, ScienceDirect, Cochrane, and China National Knowledge Infrastructure. Initially, comparing differences in BMI between exposed and non-exposed groups that weight mean difference (WMD) were used. Subsequently, the effect of famine exposure on overweight or obesity risk, which pooled relative risks (RRs), odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. RESULT: Twenty studies were included in this systematic review and meta-analysis. Compared with non-exposed group, famine exposure group significantly increased the risk of overweight (OR = 1.10, 95% CI: 1.04-1.16) and obesity (OR = 1.15, 95% CI: 1.05-1.24). Sensitivity analyses revealed no significant change in the famine exposure and BMI, the risk of overweight and obesity study when any one study was excluded. Subgroup analyses showed that age, gender, exposure type, study type, continent, famine cause and paper publication date were associated with BMI, the risk of overweight and obesity. Meta-regression analyses suggested that continent, famine cause could partially explain heterogeneity for famine exposure and BMI studies.
CONCLUSION: The systematic review and meta-analysis indicates that famine exposure during early life may increase BMI, the risk of overweight and obesity, especially for female, fetal famine exposure or subject age less than 50. Furthermore, famine exposure group the risk of overweight and obesity in cross-sectional studies, Asian studies, famine cause by natural disaster or paper published from 2015 to the present studies are higher than that of non-exposed group.

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Mesh：

Year:  2018        PMID： 29408921      PMCID： PMC5800668          DOI： 10.1371/journal.pone.0192212

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

Body mass index (BMI) was defined as weight in kilograms divided by the height of the square in meters [1], which is far more commonly used to define overweight or obesity and closely related to the degree of body fat in most settings. As the economy grows and living standards improves rapidly, the prevalence of overweight and obesity increases as well. In 2010, overweight and obesity approximately resulted in 3.8% of DALYs, 3.4 million deaths, and 3.9% of years of life lost globally [2]. Besides, overweight and obesity are critical risk factors for cardiovascular disease and linked status, including hypercholesterolemia, hypertension, type 2 diabetes, coronary heart disease, and stroke [3]. Study by Lim SS et al. [4] have suggested that unabated the rise in obesity could well response for future declines in life expectancy. Previous research had reported that, several risk factors were confirmed to be significantly associated with overweight and obesity [5], for instance, cigarette smoking, alcohol consumption, high fat dietary, physical inactivity behavior, genetic and environmental factors, various chronic diseases factors (hypertension, diabetes, dyslipidemia and so on) [6]. Recently, presenting a branch of scientific knowledge, known as the developmental origins of health and disease (DOHaD) [7], covering its concepts that human in the early stages of the development process (including the fetus, infant, childhood) experience adverse factors (uterine placental dysfunction, malnutrition, etc.) would affect adult the occurrence of obesity, diabetes, cardiovascular disease and so on. Furthermore, famine exposure during early life may alter neuroendocrine function and induce HPA axis to release excessive glucocorticoid, which would increase BMI, the risk of overweight and obesity [8]. Compelling evidence have been performed to explore the relationship between exposure to famine during early life and the risk of overweight and obesity in adulthood. However, the results are controversial. Study of GP Ravelli et al. [9] found that early life was stimulated by Dutch famine could increase obesity prevalence in adult. In addition, the majority of research had reported that the Chinese great famine brought about shorter stature and overweight in females after 50 years [10-11]. Whereas several studies indicated no significant association between famine exposure during early life and adult overweight and obesity risk, such as Li yuanbi et al and Zhao yan et al [12-13]. Therefore, we systematically conducted a systematic review and meta-analysis to explore the relation between famine exposure during early life stage and BMI in adult, and further estimate the associations between famine exposure and the risk of overweight or obesity in adulthood.

Methods

We carried out a systematic review and meta-analysis according to the Cochrane methodology and the recommendations for reporting proposed by the systematic review and meta-analysis of observational studies in epidemiology group [14] (S1 Table).

Famine definition

The criteria for the definition of famine were not consistent in each region [12], such as Chinese famine was defined as food supplement dropped by 70% with the time reported from September 30, 1959 to October 1, 1961. However, the 1944–1945 Dutch famine was defined as energy supplement less than 1000kcal every day.

Search strategy

We conducted a literature search to identify relevant available articles with English or Chinese from PubMed, ScienceDirect, Cochrane library, and China National Knowledge Infrastructure, which published up to August 2017. The search terms, including “famine” “starvation” “hunger” “undernutrition” “undernourishment” “malnutrition” “malnourishment”, “body mass index” “BMI”, after screening titles and abstracts, two reviewers independently examined full text articles and extracted data on study characteristics, quality and results. We also reviewed the reference lists from the included articles to search for further relevant studies. The flowchart of literature search was showed in Fig 1.
Fig 1

Study selection flowchart.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (1) original article was an observational study. (2) the exposure of interest was famine. (3) BMI value (mean± SD, Standard Deviation), overweight or obesity relative risks (RRs), odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs) were available, or calculated them by providing data. (4) the latest and most complete study was selected if data from the same participant had been published more than once. Articles were excluded based on the following criteria: (1) animal experiment rather than human study. (2) editorials, letters, reviews, commentaries or interviews. (3) duplicate articles. (4) irrelevant for famine exposure and BMI, the risk of overweight and obesity. (5) undefined famine exposure time. All identified studies were carefully reviewed independently by two investigators to determine whether an individual study was eligible for inclusion criteria in this study.

Data extraction

The following data were extracted: the first author’s name, study continent (region), paper publication year, study language, study design type, the average age of subjects, percentage of males (%), definition standard of obesity/overweight by using BMI, famine duration period, adjustment for covariates, famine exposure grouping, BMI value (mean± SD), overweight or obesity RRs, ORs or HRs with theirs 95% CIs.

Quality evaluation

The Newcastle-Ottawa Quality Assessment Scale was applied for literature quality evaluation [15]. Nine questions were assessed and each satisfactory answer received 1 point, causing a maximum score of 9. Only these studies in which the majority of the questions were deemed satisfactory (i.e. with a score of 6 or higher) were considered to be of high methodological quality.

Statistical analysis

All statistical analysis were performed by using STATA, version 12.0. Originally, BMI value, as continuous data, weight mean difference (WMD) was used to compare the BMI distinction between exposed and non-exposed group. Subsequently, pooled measure was calculated as the inverse variance weighted mean of the logarithm of OR (OR, RR, HR) with theirs 95% CIs to evaluate the strength of association between famine exposure and the risk of overweight or obesity. Generally, I2 was used to assess heterogeneity between studies (I2 values of 0%, 25%, 50%, and 75% represent no, low, moderate and high heterogeneity, respectively) [16]. Less than 50% of I2 was considered acceptable heterogeneity in this study. Random effect model was used to estimate the pooled effect and 95% CIs. The sensitivity analysis was performed to assess the key studies with substantial impact on the between-study heterogeneity. Subgroup analyses and meta regression analyses were carried out to further find heterogeneity source by gender, age, exposure situation, study type, continent, famine cause, paper publication date, adjusting for the confounding factors variable. Publication bias was assessed with visual inspection of the funnel plot and Egger’s test [17]. The graph were symmetrical inverted funnel-shaped or Egger's test P value more than 0.05, which indicated without bias. All reported probabilities (P values) were two-sided with a statistical significance level of 0.05.

Results

Characteristics of studies

We identified 20 published articles [10–13, 18–33], of which 17 studies with 27 data were available for each group BMI value (mean± SD), and 12 studies obtained famine exposure and the OR (OR, RR, HR) values of overweight with 27 data or obese with 42 data for this study, to estimate the relationship between famine exposure during early life and later BMI, the risk of overweight and obesity. Chinese and English study were included in this study, apart from the study of Li yuanbi et al. [12] and Zhao yan et al. [13], other 18 studies were in English. Eleven cross-sectional, six historical cohort and three prospective cohort studies were included in the present study. Among these studies, 13 studies carried out in Asia, 6 studies in Europe and 1 studies in Africa. Including 6 types famine duration period (1940–1944, 1943–1944, 1944–1945, 1959–1961, 1967–1970, 1974–1975). Fifteen studies defined overweight and obesity criteria by BMI value, of which 8 studies defined 5 kinds of overweight criteria and 8 studies defined 3 types obesity criteria. The detailed characteristics of the included studies were presented in Table 1. All studies famine exposure grouping were showed in Fig 2. Birth cohort year of the longest span was in ZN Zhang et al. [18] study, ranging from 1941 to 1980. By contrary to ZN Zhang et al. [18] study, Aryeh D. Stein et al. [19], who studied birth cohort only 15 months with the shortest time extent. In addition, Li yuanbi et al. [12] study’s birth cohort timing was consistent with Hongwei Xu et al. [20] study.
Table 1

Characteristics of studies for famine exposure included in this study.

Author (year)Continent (region)Study languageStudy designAge (mean)Males (%)Definition of Obesity/Overweight(kg/m2)Famine duration periodFamine exposure groupingAdjustment for covariates
YH Wang et al [10], (2009)Asia (Chongqing)EnglishCross-sectionalNM61.1Overweight: 25<BMI<29.9 Obesity: BMI≥301959–1961fetal, childhood exposure, nonexposureUnadjustment
L. Liu et al [11] (2017)Asia (Qingdao)EnglishCross-sectional49.938.0Overweight: 24<BMI<27.9 Obesity: BMI≥281959–1961fetal, childhood, adolescence exposure, nonexposureAge, sex, education, family obesity history, family month income, smoking, drinking, chronic disease history.
Li yuanbi et al [12], (2014)Asia (Hefei)ChineseCross-sectional52.549.0Obesity: BMI≥241959–1961fetal, childhood exposure, nonexposureFamily year income, Feeding style, Dietary intake.
Zhao yan et al [13], (2013)Asia (Hefei)ChineseCross-sectionalNM59.6Overweight: 24<BMI<27.9 Obesity: BMI≥281959–1961fetal, childhood exposure, nonexposureSex, education, smoking, family history, region, physical activities, Nutritional supplements, dietary pattern score.
ZN Zhang et al [18], (2017)Asia (Guangdong)EnglishCross-sectional51.749.1ND1959–1961childhood exposure, nonexposureUnadjustment
Aryeh D et al [19], 2009Europe (Leiden)EnglishCross-sectional59.045.3ND1944–1945fetal exposure, nonexposureUnadjustment
Hongwei Xu et al [20], (2016)Asia (Hubei)EnglishHistorical cohortNM48.3Overweight: BMI≥251959–1961fetal, childhood exposure, nonexposureUnadjustment
Martin Hult et al [21], (2010)Africa (Biafran)EnglishHistorical cohort39.761.8Overweight: 25<BMI<29.9 Obesity: BMI≥301967–1970fetal, childhood exposure, nonexposureUnadjustment
Zumin Shi et al [22], (2013)Asia (Jiangsu)EnglishCross-sectional43.045.1Overweight: BMI≥241959–1961fetal, childhood exposure, nonexposureUnadjustment
Oxana Rotar et al [23], (2015)Europe (Saint Petersburg)EnglishHistorical cohort70.727.0Obesity: BMI≥301943–1944fetal exposure, nonexposureUnadjustment
S Finer et al [24], (2016)Asia (Matlab)EnglishHistorical cohort44.5NMOverweight: BMI≥231974–1975fetal, childhood exposure, nonexposureUnadjustment
Pei-Xi Wang et al [25], (2012)Asia (Guangdong)EnglishHistorical cohort49.549.0Overweight: 24<BMI<27.9 Obesity: BMI≥281959–1961fetal, childhood exposure, nonexposureAge, education, occupation, smoking, drinking, physical activities, dietary habits, residence, hypertension history.
Cheng Huang et al [26], (2010)Asia(Hebei, Zhejiang, Jiangsu)EnglishCross-sectional31.70.0Overweight: BMI≥251959–1961fetal, childhood exposure, nonexposureUnadjustment
ZH Wang et al [27], (2016)Asia (Nationwide)EnglishCross-sectionalNM49.3Overweight: BMI≥241959–1961fetal, childhood exposure, nonexposureUnadjustment
Jing Wang et al [28], (2017)Asia (Hubei)EnglishProspective cohort56.416.8Overweight: BMI≥241959–1962fetal, childhood exposure, nonexposureUnadjustment
Lital Keinan et al [29], (2015)Europe (Jewish)EnglishCross-sectional69.349.6ND1940–1944fetal exposure, nonexposureUnadjustment
LauraS et al [30], 2016Europe (Amsterdam)EnglishProspective cohort68.045.0ND1944–1945fetal exposure, nonexposureUnadjustment
Annet F. M et al [31], (2013)Europe (Arnhem)EnglishProspective cohort59.80.0ND1944–1945fetal exposure, nonexposureUnadjustment
Anita CJ et al [32], (1999)Europe (Amsterdam)EnglishCross-sectional50.048.0Overweight:BMI≥251944–1945childhood exposure, nonexposureUnadjustment
Z.Yang et al [33], (2008)Asia (Nationwide)EnglishHistorical cohortNM45.6Overweight: 24<BMI<27.9 Obesity: BMI≥281959–1961fetal exposure, nonexposureGeographic areas

NM: Not mentioned, ND: No definition

Fig 2

All studies grouping in the famine exposure.

Red: fetal exposed, Brown: childhood exposed, Green: nonexposed.

NM: Not mentioned, ND: No definition

All studies grouping in the famine exposure.

Red: fetal exposed, Brown: childhood exposed, Green: nonexposed.

Quality assessment

The results of the literature quality evaluation were shown in S2 Table. There were 18 articles in high methodological quality, including YH Wang et al. [10], L. Liu et al. [11], Li yuanbi et al. [12], Zhao yan et al. [13], ZN Zhang et al. [18], Hongwei Xu et al. [20], Martin Hult et al. [21], Zumin Shi et al. [22], Oxana Rotar et al. [23], S Finer et al. [24], Pei-Xi Wang et al. [25], Cheng Huang et al. [26], ZH Wang et al. [27], Jing Wang et al. [28], Lital Keinan et al. [29], Laura S. et al. [30], Anita CJ et al. [32] and Z. Yang et al. [33] research. Besides, Aryeh D. et al. [19] and Annet F. M et al. [31] study had low methodological quality.

Quantitative synthesis

There were statistical distinction between famine exposed group and nonexposed group in BMI (WMD = 0.10, 95% CI: -0.04–0.24) (Fig 3). But significant difference was observed in the risk of overweight (OR = 1.10, 95% CI: 1.04–1.16) (Fig 4) and obesity (OR = 1.15, 95% CI: 1.05–1.24) (Fig 5). The results of subgroup analysis were presented in Table 2. In age subgroup analysis, there were higher BMI level (WMD = 0.33, 95% CI: 0.06–0.60) and risk of overweight (OR = 1.13, 95% CI: 1.07–1.19) or obesity (OR = 1.24, 95% CI: 1.08–1.39) in age less than 50. In gender subgroup analysis, famine exposure during early life could significantly increase BMI (WMD = 0.22, 95% CI: 0.11–0.33), the risk of overweight (OR = 1.26, 95% CI: 1.15–1.37) and obesity (OR = 1.30, 95% CI: 1.16–1.45) in female. By contrast, the result was not observed in male. In exposure type subgroup analysis, fetal exposure could increase BMI (WMD = 0.22, 95% CI: 0.05,0.38), the risk of overweight (OR = 1.11, 95% CI: 1.04–1.18) or obesity (OR = 1.15, 95% CI: 1.04–1.26) in adulthood, but the result was not found in childhood exposure. In study type subgroup, we found that cross-sectional studies, famine exposure group risk of overweight (OR = 1.12, 95% CI: 1.05–1.19) and obesity (OR = 1.20, 95% CI: 1.07–1.34) were higher than non-exposed group. In continent subgroup, we found that Asian studies, famine exposure group risk of overweight (OR = 1.11, 95% CI: 1.04–1.17) and obesity (OR = 1.15, 95% CI: 1.05–1.25) were higher than non-exposed group. In famine cause subgroup analysis, we found that natural disaster, famine exposure risk of overweight (OR = 1.11, 95% CI: 1.04–1.17) and obesity (OR = 1.15, 95% CI: 1.05–1.25) were higher than non-exposed group. In paper publication date subgroup analysis, we found that the paper published from 2015 to the present, famine exposure risk of overweight (OR = 1.09, 95% CI: 1.01–1.16) and obesity (OR = 1.30, 95% CI: 1.13–1.47) were higher than non-exposed group.
Fig 3

The forest plot of famine exposure and BMI.

Fig 4

The forest plot of famine exposure and the risk of overweight.

Fig 5

The forest plot of famine exposure and the risk of obesity.

Table 2

The subgroup analysis between famine exposure and BMI, the risk of overweight, obesity.

TypeSubgroupStudies numbersWMD (95 CI%)HeterogeneityPublication bias
χ2I2 (%)PTP
Famine exposure and BMIAll studies270.10(-0.04,0.24)130.4780.1<0.001-0.650.522
Gender
 Male3-0.21(-0.37,-0.04)2.104.80.350-1.810.670
 Female50.22(0.11,0.33)5.8231.30.2130.230.834
 Male/Female190.14(-0.10,0.38)99.4081.9<0.0010.330.777
Age
 NM5-0.36(-0.69,-0.04)12.2267.30.016-1.980.398
 ≤5070.33(0.06,0.60)11.6248.40.0710.580.425
 >50150.17(-0.03,0.38)77.5982.0<0.0010.380.808
Exposure type
 Fetal180.22(0.05,0.38)75.0277.3<0.0010.070.925
 Childhood9-0.11(-0.38,0.15)33.8876.4<0.0010.110.954
Study type
 Historical cohort60.07(-0.40,0.53)14.6565.90.0120.350.801
 Cross sectional160.06(-0.14,0.27)104.0485.6<0.001-0.640.523
 Prospective cohort50.29(0.17,0.41)2.230.00.694-1.150.197
Continent
 Asia19-0.04(-0.18,0.10)73.4475.5<0.001-1.460.307
 Africa20.59(-0.19,1.37)3.0667.30.08--
 Europe60.56(0.06,1.07)31.3684.1<0.0010.610.761
Famine cause
 Natural disaster17-0.03(-0.18,0.11)71.0677.5<0.001-1.620.043
 War100.46(0.09,0.83)39.7277.3<0.0010.060.961
Publication date
 Before 201050.34(0.02,0.66)20.1280.1<0.0011.090.509
 2011 to 2014120.02(-0.18,0.21)40.9473.1<0.001-0.740.666
 2015 to present100.05(-0.33,0.43)63.685.8<0.001-0.950.585
Famine exposure and overweightAll studies271.10(1.04,1.16)76.8466.2<0.0010.210.832
Exposure type
 Fetal141.11(1.04,1.18)23.2544.10.039-0.270.763
 Childhood131.09(0.99,1.20)51.2676.6<0.0010.760.623
Confounding
 Unadjusted181.10(1.12,1.18)59.1771.3<0.0010.640.571
 Adjusted91.11(1.02,1.20)15.1347.10.057-0.710.548
Gender
 Male71.00(0.93,1.07)7.7122.20.261.430.18
 Female71.26(1.15,1.37)12.1250.50.059-3.260.054
 Male/Female131.15(0.99,1.12)17.7932.60.122-0.320.666
Age
 NM91.05(0.98,1.21)59.0786.5<0.0010.750.872
 ≤50131.13(1.07,1.19)9.6300.648-0.180.764
 >5051.07(0.95,1.19)2.5200.642-0.090.961
Study type
 Cross sectional191.12(1.05,1.19)47.9262.4<0.0010.760.475
 Historical cohort81.05(0.92,1.18)28.2175.2<0.001-0.630.691
Continent
 Asia251.11(1.04,1.17)75.9468.4<0.0010.390.702
 Africa11.02(0.73,1.31)-----
 Europe10.98(0.77,1.20)-----
Famine cause
 Natural disaster231.11(1.04,1.17)75.170.7<0.0010.270.808
 War41.00(0.84,1.17)0.9900.8030.850.402
Publication date
 Before 201091.12(1.01,1.23)48.6183.5<0.0011.150.709
 2011 to 201421.07(0.94,1.21)0.3100.576--
 2015 to present161.09(1.01,1.16)27.8246.10.023-0.060.939
Famine exposure and obesityAll studies421.15(1.05,1.24)127.567.8<0.001-0.940.353
Exposure type
 Fetal231.15(1.04,1.26)47.79540.001-0.460.523
 Childhood191.15(0.99,1.31)78.3777<0.001-0.630.526
Confounding
 Unadjusted231.12(1.00,1.25)84.5974<0.001-0.720.457
 Adjusted191.18(1.04,1.32)40.1555.20.002-0.480.483
Gender
 Male150.93(0.84,1.03)23.1439.50.0580.670.42
 Female151.30(1.16,1.45)26.3846.90.023-1.40.061
 Male/Female121.21(1.081.35)18.63410.068-1.170.086
Age
 NM111.04(0.92,1.15)19.4848.70.035-0.460.644
 ≤50171.24(1.08,1.39)68.4576.6<0.001-2.670.07
 >50141.26(0.90,1.35)26.3950.70.015-0.150.856
Study type
 Cross sectional281.20(1.07,1.34)91.4770.5<0.001-0.310.648
 Historical cohort141.07(0.95,1.19)34.3262.10.001-1.880.164
Continent
 Asia391.15(1.05,1.25)124.8369.6<0.001-0.820.417
 Africa21.24(0.94,1.55)0.100.749--
 Europe10.78(0.31,1.26)-----
Famine cause
 Natural disaster391.15(1.05,1.25)124.8369.6<0.001-0.50.417
 War31.11(0.81,1.40)2.6424.20.267-3.620.221
Publication date
 Before 201091.09(0.99,1.32)19.5659.10.0121.530.389
 2011 to 2014120.99(0.85,1.13)21.4848.80.029-1.620.202
 2015 to present211.30(1.13,1.47)62.8168.2<0.001-0.710.277

WMD: weight mean difference, OR: odds ratio, NM: Not mentioned, -: indicates no. The pooled effect size was estimated using random-effects model.

WMD: weight mean difference, OR: odds ratio, NM: Not mentioned, -: indicates no. The pooled effect size was estimated using random-effects model. In order to further seek heterogeneity source, sensitivity analysis and meta-regression were performed. Sensitivity analysis revealed no significant change in the famine exposure and BMI, the risk of overweight or obesity when any one study was excluded (S1–S3 Figs). To consider the variation by study quality, sensitivity analysis was performed in high-quality studies. The result indicated no significant difference in the famine and BMI when any one high-quality study was excluded (S4 Fig). Thus, we eventually use meta-regression to find the source of heterogeneity (Table 3). In famine exposure and BMI studies, the 41.05% and 35.94% origin of heterogeneity could be explained due to the continent (P = 0.008) and famine cause (P = 0.02). But for famine exposure and the risk of overweight or obesity, the result demonstrated that no covariate conferred a significant impact on between-study heterogeneity.
Table 3

Meta-regression to find the results of heterogeneity.

TypeCovariatesβSETP>| T |95%CIAdjusted R2(%)
Famine and BMIGender0.130.150.850.403-0.18, 0.44-1.06
Age0.210.131.650.111-0.05,0.4811.25
Group-0.320.22-1.470.153-0.77, -0.1312.33
Study design0.0910.180.510.615-0.28, 0.46-4.09
Continent0.340.122.880.0080.096, 0.5841.05
Famine cause0.520.212.490.0200.09, 0.9635.94
Publication date-0.150.15-0.970.339-0.46, 0.16-5.29

β: Regression coefficients, SE: Standard error of regression coefficients, Adjusted R2(%): the current covariate can explain the size of heterogeneity.

β: Regression coefficients, SE: Standard error of regression coefficients, Adjusted R2(%): the current covariate can explain the size of heterogeneity. The funnel plot showed no evidence of significant small-study effect for the analysis BMI, the risk of overweight or obesity between nonexposed group and famine exposure (S5–S7 Figs). In addition, Egger’s test suggested no significant publication bias as a whole (P > 0.05) (Table 2).

Discussion

As noted above, this is the first systematic review and meta-analysis to evaluate the association of famine exposure during early life with the BMI in adulthood. Our studies showed that exposure to famine during early stage significant correlation to BMI, the risk of overweight and obesity, which were consistent with Wang Y H et al. [10] and Liu L et al. [11] studies. In subgroup analysis, our study suggested that exposure to famine during early life contributed to the increase of BMI, the risk of overweight and obesity in adulthood, which were positive association with female subjects studies, fetal exposure studies, subject age less than 50 studies, sectional-cross studies, Asian studies, famine cause by natural disaster and paper published from 2015 to the present studies. Furthermore, the meta-regression results intimated that continent and famine cause could contribute to explaining partial heterogeneity for famine exposure and BMI studies. The mechanisms of famine exposure during early life and increased BMI in adult are still not clear now. Nevertheless, several plausible biological explanations have been reported. GE Miller et al. [34] study pointed out that, people suffered from famine stress early stage in its life that would activate the HPA axis to regulate appetite behavior. Early life formatted this nerve pathway, which would form adverse phenotypes for the future, and seek out appetite stimulating in nerve impulse way. Therefore, individuals tend to engage in health hazards behavior such as high fat diet, high-energy food and physical inactivity. As we know, energy intake and consumption simultaneously exists in the body, when the long-term energy intake are greater than the consumption, and it allows the energy to accumulate in the form of adipose in vivo, especially for long-term intake of excess saturated fatty acids, trans fatty acids and cholesterol. Enduring positive energy balance further elevates BMI value, which would lead to overweight or obesity later. Study of Heidi P et al. [35] indicated that, the early stress of life was controlled by epigenetic markers that regulated histones, post-translational modifications and tissue remodeling into macrophages. Thus, these cells possessed proinflammatory tendencies and manifested as decreased responses of cytokines for sex hormones inhibitor susceptibility. In the course of life, these proinflammatory trends were exacerbated by behavior and tended to own hormonal disorders, which was the product of exposure to early stress. In the act, life early stress caused excessive threat of vigilance, lack of interpersonal relationships, self-regulation dysfunction. Additionally, postnatal accelerated “growth” or “catch-up growth” hypothesis had also suggested that increased growth rate by a nutrient-enriched diet might bring about overweight or obesity [36]. Our study indicated that there was a significant increase in overweight and obesity risk in women subjects who experienced malnutrition during early life. But the result not observed in men subjects, which was in line with other studies [32-33]. Possible reasons were as follows: firstly, a study noted that women who were exposed to famine had a higher risk of overeating than men [37]. Thus, it may increase adult BMI and then increase the risk of overweight and obesity. Secondly, women deposit fat in the abdomen [38-39], and intraabdominal obesity is related to low testosterone concentrations in male and hyperandrogenicity in female [40]. Therefore, the potential obesity mechanisms are commonly classified into 2 regimentations [41]. The first category is hypothalamic dysfunction, and the second category is abnormal levels of fat cells. Follow this view, we think our findings suggesting that the different roles in male and female support the notion that the increased level of obesity after exposure to hunger early in pregnancy are due to functional changes in the central endocrine regulatory machinery rather than to fat cell abnormalities. In addition, we found that fetal famine exposure during early life could significantly increase BMI, the risk of overweight or obesity in adulthood, but the result was not observed in childhood famine exposure. According to DOHaD hypothesis [7], famine exposure during early stages could change the structure and function of important tissues and organs. It is an relatively irreversible process in the fetal exposure, but reversible process in childhood exposure. Increasing evidence suggest that age and BMI form an inverted U-shaped relationship [42-43]. Thus, we study found that there were higher BMI level and risk of overweight or obesity in age less than 50. In cross-sectional studies, famine exposure groups overweight and obesity risks were higher than non-exposed groups. Possible reason as follow: firstly, the cross-sectional study was grouped after the data was collected. In other words, there were natural controls in the same period, so it was comparable. Secondly, the sample came from the same target population, and randomly selected a representative sample to describe the association between exposure and the outcome, so the research results had a stronger promotion. In Asian studies, famine exposure groups overweight and obesity risks were higher than non-exposed groups. Available explanation were numbers of study, and the number in Asian were relatively more than in European and African. And also the definition criterion of overweight and obesity in Europe and Africa are higher than in Asia [44-45]. Compared with the non-exposed group, the famine caused natural disasters in the risk of overweight or obesity was higher than famine caused by the war. We speculated that the famine caused by natural disasters was more severe than the famine caused by the war. Thus, natural disasters famine exposure in early stages was more harmful to organ and tissue. Interestingly, we found paper published from 2015 to the present that famine exposure groups overweight and obesity risks were higher than non-exposed groups. To our knowledge, there were least bias in the recent paper publication, so it was more convincing and reliable. In addition, the included study numbers may have some impact on the outcomes. According to Béjar LM et al. [46] study, Asia and Africa diet were rich in high dietary fiber, high carbohydrate, and Europe diets mainly were rich in high-fat, so it could explain some heterogeneity source. In addition, the continent led to suffering from famine exposure time were different, which may be heterogeneity source. Famine cause contained natural disaster and war in the included study, most famine studies were caused by natural disasters. Thus, it was likely to be partial heterogeneous source. This systematic review and meta-analysis has several strengths. Firstly, compared with original individual study, our study synthesized multiple famine types such as Chinese great famine, Dutch famine, Biafran war famine, Leningrad siege famine, Bangladeshi famine, Jewish Holocaust famine, enhancing statistical power to provide more precise and reliable results. Secondly, considering the potential differences of famine exposure in fetal period and childhood period, we further explored the effects of these two periods of famine exposure on BMI, the risk of overweight and obesity. Thirdly, due to the subsurface heterogeneity, we further explored the relationship between famine exposure and BMI, overweight or obesity by gender, study design type, continent, famine cause, paper publication date, adjustment for confounding factors subgroup. Therefore, the results were more reasonable and convincing. Furthermore, funnel plot and Egger’s test showed the publication bias was undetected, indicating that the included results may be unbiased. However, several potential limitations in our study should be considered. Firstly, famine duration period were not consistent across all included studies, ranging from 1 to 5 years, which may influence the stability of our results. Secondly, the degree of famine exposure was not provided in original article. Thus, we could not analysis the relation between the severity of famine exposure and BMI, the risk of overweight or obesity. Thirdly, the criteria were not the same for overweight and obesity defined in the literature, which were likely to exaggerate or reduce the impact of famine exposure on overweight and obesity in individual studies. Fourthly, due to some low quality articles or little literature about famine and overweight risk, which may reduce the efficiency of research. Finally, this only is a systematic review and meta-analyses, and the underlying mechanism needs a large population data and animal testing to verification.

Conclusion

In summary, results from this systematic review and meta-analyses show that famine exposure during early life significantly increased BMI, the risk of overweight and obesity especially for subjects being adult female, exposure type being fetal period and subject age being less than 50. Furthermore, famine exposure increase the risk of overweight and obesity, which are strongly associated with cross-sectional studies, natural disasters studies, Asian studies and paper published from 2015 to the present studies.

sensitivity analysis of famine exposure and BMI.

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sensitivity analysis of famine exposure and overweight risk.

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sensitivity analysis of famine exposure and obesity risk.

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sensitivity analysis of famine exposure and BMI in high-quality studies.

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funnel plot of famine exposure and BMI.

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funnel plot of famine exposure and overweight risk.

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funnel plot of famine exposure and obesity risk.

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Quality Evaluation.

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PRISMA Checklist.

PRISMA 2009 Checklist. (PDF) Click here for additional data file. (XLSX) Click here for additional data file.
  43 in total

1.  Exposure to famine in early life and the risk of obesity in adulthood in Qingdao: Evidence from the 1959-1961 Chinese famine.

Authors:  L Liu; Z C Pang; J P Sun; B Xue; S J Wang; F Ning; Q Qiao
Journal:  Nutr Metab Cardiovasc Dis       Date:  2016-12-05       Impact factor: 4.222

Review 2.  Measuring the full economic costs of diet, physical activity and obesity-related chronic diseases.

Authors:  B M Popkin; S Kim; E R Rusev; S Du; C Zizza
Journal:  Obes Rev       Date:  2006-08       Impact factor: 9.213

3.  Chronic health conditions in Jewish Holocaust survivors born during World War II.

Authors:  Lital Keinan-Boker; Hadas Shasha-Lavsky; Sofia Eilat-Zanani; Adi Edri-Shur; Shaul M Shasha
Journal:  Isr Med Assoc J       Date:  2015-04       Impact factor: 0.892

4.  Obesity: impact of cardiovascular disease.

Authors:  R M Krauss; M Winston; R N Fletcher; S M Grundy
Journal:  Circulation       Date:  1998-10-06       Impact factor: 29.690

5.  Mechanisms of developmental programming of the metabolic syndrome and related disorders.

Authors:  Zhong-Cheng Luo; Lin Xiao; Anne-Monique Nuyt
Journal:  World J Diabetes       Date:  2010-07-15

6.  Prevalence of overweight and obesity and their association with hypertension and diabetes mellitus in an Indo-Asian population.

Authors:  Tazeen H Jafar; Nish Chaturvedi; Gregory Pappas
Journal:  CMAJ       Date:  2006-10-24       Impact factor: 8.262

7.  A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010.

Authors:  Stephen S Lim; Theo Vos; Abraham D Flaxman; Goodarz Danaei; Kenji Shibuya; Heather Adair-Rohani; Markus Amann; H Ross Anderson; Kathryn G Andrews; Martin Aryee; Charles Atkinson; Loraine J Bacchus; Adil N Bahalim; Kalpana Balakrishnan; John Balmes; Suzanne Barker-Collo; Amanda Baxter; Michelle L Bell; Jed D Blore; Fiona Blyth; Carissa Bonner; Guilherme Borges; Rupert Bourne; Michel Boussinesq; Michael Brauer; Peter Brooks; Nigel G Bruce; Bert Brunekreef; Claire Bryan-Hancock; Chiara Bucello; Rachelle Buchbinder; Fiona Bull; Richard T Burnett; Tim E Byers; Bianca Calabria; Jonathan Carapetis; Emily Carnahan; Zoe Chafe; Fiona Charlson; Honglei Chen; Jian Shen Chen; Andrew Tai-Ann Cheng; Jennifer Christine Child; Aaron Cohen; K Ellicott Colson; Benjamin C Cowie; Sarah Darby; Susan Darling; Adrian Davis; Louisa Degenhardt; Frank Dentener; Don C Des Jarlais; Karen Devries; Mukesh Dherani; Eric L Ding; E Ray Dorsey; Tim Driscoll; Karen Edmond; Suad Eltahir Ali; Rebecca E Engell; Patricia J Erwin; Saman Fahimi; Gail Falder; Farshad Farzadfar; Alize Ferrari; Mariel M Finucane; Seth Flaxman; Francis Gerry R Fowkes; Greg Freedman; Michael K Freeman; Emmanuela Gakidou; Santu Ghosh; Edward Giovannucci; Gerhard Gmel; Kathryn Graham; Rebecca Grainger; Bridget Grant; David Gunnell; Hialy R Gutierrez; Wayne Hall; Hans W Hoek; Anthony Hogan; H Dean Hosgood; Damian Hoy; Howard Hu; Bryan J Hubbell; Sally J Hutchings; Sydney E Ibeanusi; Gemma L Jacklyn; Rashmi Jasrasaria; Jost B Jonas; Haidong Kan; John A Kanis; Nicholas Kassebaum; Norito Kawakami; Young-Ho Khang; Shahab Khatibzadeh; Jon-Paul Khoo; Cindy Kok; Francine Laden; Ratilal Lalloo; Qing Lan; Tim Lathlean; Janet L Leasher; James Leigh; Yang Li; John Kent Lin; Steven E Lipshultz; Stephanie London; Rafael Lozano; Yuan Lu; Joelle Mak; Reza Malekzadeh; Leslie Mallinger; Wagner Marcenes; Lyn March; Robin Marks; Randall Martin; Paul McGale; John McGrath; Sumi Mehta; George A Mensah; Tony R Merriman; Renata Micha; Catherine Michaud; Vinod Mishra; Khayriyyah Mohd Hanafiah; Ali A Mokdad; Lidia Morawska; Dariush Mozaffarian; Tasha Murphy; Mohsen Naghavi; Bruce Neal; Paul K Nelson; Joan Miquel Nolla; Rosana Norman; Casey Olives; Saad B Omer; Jessica Orchard; Richard Osborne; Bart Ostro; Andrew Page; Kiran D Pandey; Charles D H Parry; Erin Passmore; Jayadeep Patra; Neil Pearce; Pamela M Pelizzari; Max Petzold; Michael R Phillips; Dan Pope; C Arden Pope; John Powles; Mayuree Rao; Homie Razavi; Eva A Rehfuess; Jürgen T Rehm; Beate Ritz; Frederick P Rivara; Thomas Roberts; Carolyn Robinson; Jose A Rodriguez-Portales; Isabelle Romieu; Robin Room; Lisa C Rosenfeld; Ananya Roy; Lesley Rushton; Joshua A Salomon; Uchechukwu Sampson; Lidia Sanchez-Riera; Ella Sanman; Amir Sapkota; Soraya Seedat; Peilin Shi; Kevin Shield; Rupak Shivakoti; Gitanjali M Singh; David A Sleet; Emma Smith; Kirk R Smith; Nicolas J C Stapelberg; Kyle Steenland; Heidi Stöckl; Lars Jacob Stovner; Kurt Straif; Lahn Straney; George D Thurston; Jimmy H Tran; Rita Van Dingenen; Aaron van Donkelaar; J Lennert Veerman; Lakshmi Vijayakumar; Robert Weintraub; Myrna M Weissman; Richard A White; Harvey Whiteford; Steven T Wiersma; James D Wilkinson; Hywel C Williams; Warwick Williams; Nicholas Wilson; Anthony D Woolf; Paul Yip; Jan M Zielinski; Alan D Lopez; Christopher J L Murray; Majid Ezzati; Mohammad A AlMazroa; Ziad A Memish
Journal:  Lancet       Date:  2012-12-15       Impact factor: 79.321

8.  Obesity criteria for identifying metabolic risks.

Authors:  Jin-wen Wang; Da-yi Hu; Yi-hong Sun; Jia-hong Wang; Gui-lian Wang; Jiang Xie; Zi-qiang Zhou
Journal:  Asia Pac J Clin Nutr       Date:  2009       Impact factor: 1.662

9.  Fetal malnutrition and long-term outcomes.

Authors:  Caroline H D Fall
Journal:  Nestle Nutr Inst Workshop Ser       Date:  2013-07-18

10.  Exposure to Famine at a Young Age and Unhealthy Lifestyle Behavior Later in Life.

Authors:  Heidi P Fransen; Petra H M Peeters; Joline W J Beulens; Jolanda M A Boer; G Ardine de Wit; N Charlotte Onland-Moret; Yvonne T van der Schouw; H Bas Bueno-de-Mesquita; Jeljer Hoekstra; Sjoerd G Elias; Anne M May
Journal:  PLoS One       Date:  2016-05-31       Impact factor: 3.240
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  12 in total

1.  Early life famine exposure and anthropometric profile in adulthood: a systematic review and Meta-analysis.

Authors:  Getachew Arage; Tefera Belachew; Kalkidan Hassen Abate
Journal:  BMC Nutr       Date:  2022-04-22

2.  The Relationship Between Famine Exposure During Early Life and Left Ventricular Hypertrophy in Adulthood.

Authors:  Yu-Qin Yan; Lin Liu; Shuo Sun; Ying-Qing Feng; Jie Li; Yu-Qing Huang
Journal:  Front Nutr       Date:  2022-05-31

3.  Fetal Exposure to Chinese Famine Increases Obesity Risk in Adulthood.

Authors:  Chao Song; Meng Wang; Zheng Chen; Yecheng Yao; Ganyu Feng; Yanning Ma; Jing Fan; Ailing Liu
Journal:  Int J Environ Res Public Health       Date:  2020-05-22       Impact factor: 3.390

Review 4.  Effect of Exposure to Famine during Early Life on Risk of Metabolic Syndrome in Adulthood: A Meta-Analysis.

Authors:  Lu-Lu Qin; Bang-An Luo; Fan Gao; Xiang-Lin Feng; Jia-He Liu
Journal:  J Diabetes Res       Date:  2020-03-05       Impact factor: 4.011

Review 5.  Omics Biomarkers in Obesity: Novel Etiological Insights and Targets for Precision Prevention.

Authors:  Krasimira Aleksandrova; Caue Egea Rodrigues; Anna Floegel; Wolfgang Ahrens
Journal:  Curr Obes Rep       Date:  2020-09

6.  The Impact of Harsh Parenting on the Development of Obesity in Adulthood: An Examination of Epigenetic/Gene Expression Mediators Among African American Youth.

Authors:  Man-Kit Lei; Steven R H Beach; Ronald L Simons; Kaixiong Ye
Journal:  Front Cardiovasc Med       Date:  2021-11-05

7.  Early Life Exposure to Food Insecurity is Associated with Changes in BMI During Childhood Among Latinos from CHAMACOS.

Authors:  Ryan J Gamba; Brenda Eskenazi; Kristine Madsen; Alan Hubbard; Kim Harley; Barbara A Laraia
Journal:  J Immigr Minor Health       Date:  2021-01-02

8.  Famine Exposure in Early Life and Risk of Metabolic Syndrome in Adulthood: Comparisons of Different Metabolic Syndrome Definitions.

Authors:  Feng Ning; Jie Ren; Xin Song; Dong Zhang; Li Liu; Lei Zhang; Jianping Sun; Dongfeng Zhang; Zengchang Pang; Qing Qiao; On Behalf Of Qingdao Diabetes Prevention Program
Journal:  J Diabetes Res       Date:  2019-12-06       Impact factor: 4.011

9.  Consequences of a Great Crisis on Chronic Diseases: How Childhood Exposures May Shape Future Health.

Authors:  Jason J Lee; Zumin Shi
Journal:  Arthritis Rheumatol       Date:  2021-03-11       Impact factor: 15.483

10.  Combined Effect of Famine Exposure and Obesity Parameters on Hypertension in the Midaged and Older Adult: A Population-Based Cross-Sectional Study.

Authors:  Lin Zhang; Liu Yang; Congzhi Wang; Ting Yuan; Dongmei Zhang; Huanhuan Wei; Jing Li; Yunxiao Lei; Lu Sun; Xiaoping Li; Ying Hua; Hengying Che; Yuanzhen Li
Journal:  Biomed Res Int       Date:  2021-09-23       Impact factor: 3.411
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